Multi-algorithmic approach to enhancing the accuracy of iris recognition system is proposed and investigated. In this system, features are extracted from the iris using various feature extraction algorithms, namely LPQ, LBP, Gabor Filter, Haar, Db8 and Db16. Based on the experimental results, it is demonstrated that Mutli-algorithms Iris Recognition System is performing better than the unimodal system. The accuracy improvement offered by the proposed approach also showed that using more than two feature extraction algorithms in extracting the iris system might decrease the system performance. This is due to redundant features. The paper presents a detailed description of the experiments and provides an analysis of the performance of the proposed method.
Evaluation of Iris Recognition System on Multiple Feature Extraction Algorith...Editor IJCATR
Multi-algorithmic approach to enhancing the accuracy of iris recognition system is proposed and
investigated. In this system, features are extracted from the iris using various feature extraction algorithms,
namely LPQ, LBP, Gabor Filter, Haar, Db8 and Db16. Based on the experimental results, it is demonstrated
that Mutli-algorithms Iris Recognition System is performing better than the unimodal system. The accuracy
improvement offered by the proposed approach also showed that using more than two feature extraction
algorithms in extracting the iris system might decrease the system performance. This is due to redundant
features. The paper presents a detailed description of the experiments and provides an analysis of the
performance of the proposed method.
Transform Domain Based Iris Recognition using EMD and FFTIOSRJVSP
Iris is one of the physiological trait which is used to identify the individuals. In this paper Transform Domain Based Iris Recognition using EMD and FFT is proposed. Circular Hough Transform is used in the Preprocessing stage to extract circular part of eye. The circular iris part is converted into rectangular rubber sheet model in Region of Interest (ROI).Empirical Mode Functions (EMF)’s are obtained by applying Empirical Mode Decomposition (EMD) on the Iris. FFT is also applied on ROI to extract the features. These features are added arithmetically to obtain final features. The features of the database are compared with test iris using Euclidian Distance(ED) to compute performance parameters. It is observed that the values of CRR and EER are better in the case of propsed algorithm compared to existing algorithms.
Security for Identity Based Identification using Water Marking and Visual Cry...IRJET Journal
This document discusses using watermarking and visual cryptography for secure identity-based authentication. It proposes embedding an iris image using a watermarking algorithm and visual cryptography techniques for protection. Feature extraction and binomial distribution analysis are used to evaluate false acceptance and rejection rates to validate two algorithms, MASEK and Ma, for iris recognition on noisy images. The document also discusses discrete cosine transform (DCT) and discrete wavelet transform (DWT) techniques for image processing and compression in iris recognition systems.
IJERD (www.ijerd.com) International Journal of Engineering Research and Devel...IJERD Editor
The document describes a proposed algorithm called Fusion of Hybrid Domain features for Iris Recognition (FHDIR).
The algorithm pre-processes iris images by resizing, binarization, cropping and splitting them. It then applies Fast Fourier Transform (FFT) to the left half of the iris image to extract features and applies Principal Component Analysis (PCA) to the right half to extract features. These feature sets are then fused using arithmetic addition to generate a final feature vector. Test iris features are compared to the database using Euclidean Distance for identification.
The proposed algorithm is evaluated on the CASIA iris database and is found to have better performance than existing algorithms in terms of false rejection rate, false acceptance rate, and true
International Journal of Computer Science, Engineering and Information Techno...ijcseit
International Journal of Computer Science, Engineering and Information Technology (IJCSEIT) will provide an excellent international forum for sharing knowledge and results in theory, methodology and applications of Computer Science, Engineering and Information Technology. The Journal looks for significant contributions to all major fields of the Computer Science and Information Technology in theoretical and practical aspects. The aim of the Journal is to provide a platform to the researchers and practitioners from both academia as well as industry to meet and share cutting-edge development in the field.
The Biometric Algorithm based on Fusion of DWT Frequency Components of Enhanc...CSCJournals
The biometrics are used to authenticate a person effectively compared to conventional methods of identification. In this paper we propose the biometric algorithm based on fusion of Discrete Wavelet Transform(DWT) frequency components of enhanced iris image.The iris template is extracted from an eye image by considering horizontal pixels in an iris part.The iris template contrast is enhanced using Adaptive Histogram Equalization (AHE) and Histogram Equalization (HE).The DWT is applied on enhanced iris template.The features are formed by straight line fusion of low and high frequency coefficients of DWT.The Euclidian distance is used to compare final test features with database features. It is observed that the performance parameters are better in the case of proposed algorithm compared to existing algorithms.
A Novel Approach for Detecting the IRIS CryptsIJERDJOURNAL
ABSTRACT:- The iris is a stable biometric trait that has been widely used for human recognition in various applications. However, deployment of iris recognition in forensic applications has not been reported. A primary reason is the lack of human friendly techniques for iris comparison. To further promote the use of iris recognition in forensics, the similarity between irises should be made visualizable and interpretable. Recently, a human-in-the-loop iris recognition system was developed, based on detecting and matching iris crypts. Building on this framework, we propose a new approach for detecting and matching iris crypts automatically. Our detection method is able to capture iris crypts of various sizes. Our matching scheme is designed to handle potential topological changes in the detection of the same crypt in different images. Our approach outperforms the known visible-feature-based iris recognition method on three different data sets. After iris Crypts detection, Iris images were taken before and after the treatment of eye disease and the output shows the mathematical difference obtained from treatment. Gabor filter is used to extract the features. This iris recognition was effectively withstood with most ophthalmic disease like corneal oedema, iridotomies and conjunctivitis. This proposed iris recognition should be used to solve the potential problems that could cause in key biometric technology and medical diagnosis
A robust iris recognition method on adverse conditionsijcseit
As a stable biometric system, iris has recently attracted great attention among the researchers. However,
research is still needed to provide appropriate solutions to ensure the resistance of the system against error
factors. The present study has tried to apply a mask to the image so that the unexpected factors affecting
the location of the iris can be removed. So, pupil localization will be faster and robust. Then to locate the
exact location of the iris, a simple stage of boundary displacement due to the Canny edge detector has been
applied. Then, with searching left and right IRIS edge point, outer radios of IRIS will be detect. Through
the process of extracting the iris features, it has been sought to obtain the distinctive iris texture features by
using a discrete stationary wavelets transform 2-D (DSWT2). Using DSWT2 tool and symlet 4 wavelet,
distinctive features are extracted. To reduce the computational cost, the features obtained from the
application of the wavelet have been investigated and a feature selection procedure, using similarity
criteria, has been implemented. Finally, the iris matching has been performed using a semi-correlation
criterion. The accuracy of the proposed method for localization on CASIA-v1, CASIA-v3 is 99.73%,
98.24% and 97.04%, respectively. The accuracy of the feature extraction proposed method for CASIA3 iris
images database is 97.82%, which confirms the efficiency of the proposed method.
Evaluation of Iris Recognition System on Multiple Feature Extraction Algorith...Editor IJCATR
Multi-algorithmic approach to enhancing the accuracy of iris recognition system is proposed and
investigated. In this system, features are extracted from the iris using various feature extraction algorithms,
namely LPQ, LBP, Gabor Filter, Haar, Db8 and Db16. Based on the experimental results, it is demonstrated
that Mutli-algorithms Iris Recognition System is performing better than the unimodal system. The accuracy
improvement offered by the proposed approach also showed that using more than two feature extraction
algorithms in extracting the iris system might decrease the system performance. This is due to redundant
features. The paper presents a detailed description of the experiments and provides an analysis of the
performance of the proposed method.
Transform Domain Based Iris Recognition using EMD and FFTIOSRJVSP
Iris is one of the physiological trait which is used to identify the individuals. In this paper Transform Domain Based Iris Recognition using EMD and FFT is proposed. Circular Hough Transform is used in the Preprocessing stage to extract circular part of eye. The circular iris part is converted into rectangular rubber sheet model in Region of Interest (ROI).Empirical Mode Functions (EMF)’s are obtained by applying Empirical Mode Decomposition (EMD) on the Iris. FFT is also applied on ROI to extract the features. These features are added arithmetically to obtain final features. The features of the database are compared with test iris using Euclidian Distance(ED) to compute performance parameters. It is observed that the values of CRR and EER are better in the case of propsed algorithm compared to existing algorithms.
Security for Identity Based Identification using Water Marking and Visual Cry...IRJET Journal
This document discusses using watermarking and visual cryptography for secure identity-based authentication. It proposes embedding an iris image using a watermarking algorithm and visual cryptography techniques for protection. Feature extraction and binomial distribution analysis are used to evaluate false acceptance and rejection rates to validate two algorithms, MASEK and Ma, for iris recognition on noisy images. The document also discusses discrete cosine transform (DCT) and discrete wavelet transform (DWT) techniques for image processing and compression in iris recognition systems.
IJERD (www.ijerd.com) International Journal of Engineering Research and Devel...IJERD Editor
The document describes a proposed algorithm called Fusion of Hybrid Domain features for Iris Recognition (FHDIR).
The algorithm pre-processes iris images by resizing, binarization, cropping and splitting them. It then applies Fast Fourier Transform (FFT) to the left half of the iris image to extract features and applies Principal Component Analysis (PCA) to the right half to extract features. These feature sets are then fused using arithmetic addition to generate a final feature vector. Test iris features are compared to the database using Euclidean Distance for identification.
The proposed algorithm is evaluated on the CASIA iris database and is found to have better performance than existing algorithms in terms of false rejection rate, false acceptance rate, and true
International Journal of Computer Science, Engineering and Information Techno...ijcseit
International Journal of Computer Science, Engineering and Information Technology (IJCSEIT) will provide an excellent international forum for sharing knowledge and results in theory, methodology and applications of Computer Science, Engineering and Information Technology. The Journal looks for significant contributions to all major fields of the Computer Science and Information Technology in theoretical and practical aspects. The aim of the Journal is to provide a platform to the researchers and practitioners from both academia as well as industry to meet and share cutting-edge development in the field.
The Biometric Algorithm based on Fusion of DWT Frequency Components of Enhanc...CSCJournals
The biometrics are used to authenticate a person effectively compared to conventional methods of identification. In this paper we propose the biometric algorithm based on fusion of Discrete Wavelet Transform(DWT) frequency components of enhanced iris image.The iris template is extracted from an eye image by considering horizontal pixels in an iris part.The iris template contrast is enhanced using Adaptive Histogram Equalization (AHE) and Histogram Equalization (HE).The DWT is applied on enhanced iris template.The features are formed by straight line fusion of low and high frequency coefficients of DWT.The Euclidian distance is used to compare final test features with database features. It is observed that the performance parameters are better in the case of proposed algorithm compared to existing algorithms.
A Novel Approach for Detecting the IRIS CryptsIJERDJOURNAL
ABSTRACT:- The iris is a stable biometric trait that has been widely used for human recognition in various applications. However, deployment of iris recognition in forensic applications has not been reported. A primary reason is the lack of human friendly techniques for iris comparison. To further promote the use of iris recognition in forensics, the similarity between irises should be made visualizable and interpretable. Recently, a human-in-the-loop iris recognition system was developed, based on detecting and matching iris crypts. Building on this framework, we propose a new approach for detecting and matching iris crypts automatically. Our detection method is able to capture iris crypts of various sizes. Our matching scheme is designed to handle potential topological changes in the detection of the same crypt in different images. Our approach outperforms the known visible-feature-based iris recognition method on three different data sets. After iris Crypts detection, Iris images were taken before and after the treatment of eye disease and the output shows the mathematical difference obtained from treatment. Gabor filter is used to extract the features. This iris recognition was effectively withstood with most ophthalmic disease like corneal oedema, iridotomies and conjunctivitis. This proposed iris recognition should be used to solve the potential problems that could cause in key biometric technology and medical diagnosis
A robust iris recognition method on adverse conditionsijcseit
As a stable biometric system, iris has recently attracted great attention among the researchers. However,
research is still needed to provide appropriate solutions to ensure the resistance of the system against error
factors. The present study has tried to apply a mask to the image so that the unexpected factors affecting
the location of the iris can be removed. So, pupil localization will be faster and robust. Then to locate the
exact location of the iris, a simple stage of boundary displacement due to the Canny edge detector has been
applied. Then, with searching left and right IRIS edge point, outer radios of IRIS will be detect. Through
the process of extracting the iris features, it has been sought to obtain the distinctive iris texture features by
using a discrete stationary wavelets transform 2-D (DSWT2). Using DSWT2 tool and symlet 4 wavelet,
distinctive features are extracted. To reduce the computational cost, the features obtained from the
application of the wavelet have been investigated and a feature selection procedure, using similarity
criteria, has been implemented. Finally, the iris matching has been performed using a semi-correlation
criterion. The accuracy of the proposed method for localization on CASIA-v1, CASIA-v3 is 99.73%,
98.24% and 97.04%, respectively. The accuracy of the feature extraction proposed method for CASIA3 iris
images database is 97.82%, which confirms the efficiency of the proposed method.
IRDO: Iris Recognition by fusion of DTCWT and OLBPIJERA Editor
This document proposes a new iris recognition method called IRDO that fuses Dual Tree Complex Wavelet Transform (DTCWT) and Overlapping Local Binary Pattern (OLBP) features. DTCWT is used to extract micro-texture features from the iris, while OLBP enhances the extraction of edge features. Fusing these two methods results in improved matching performance and classification accuracy compared to state-of-the-the-art techniques. The proposed IRDO method achieves higher iris recognition rates as measured by Total Success Rate and Equal Error Rate.
International Journal of Engineering Research and Development (IJERD)IJERD Editor
International Journal of Engineering Research and Development is an international premier peer reviewed open access engineering and technology journal promoting the discovery, innovation, advancement and dissemination of basic and transitional knowledge in engineering, technology and related disciplines.
Biometric Iris Recognition Based on Hybrid Techniqueijsc
This document presents a study on implementing an iris recognition system using a hybrid technique. The system utilizes several image processing and machine learning techniques. It begins with preprocessing the iris image, including capturing, resizing and converting to grayscale. Histogram equalization is then used for enhancement. Two-dimensional discrete wavelet transform (2D DWT) is applied for feature extraction. Various edge detection algorithms including Canny, Prewitt, Roberts and Sobel are used to detect iris boundaries. The features are then stored in a vector for classification. The system is tested on different iris images and analysis shows 2D DWT and Canny edge detection provide adequate results for feature extraction and iris recognition.
International Journal of Computational Engineering Research(IJCER)ijceronline
International Journal of Computational Engineering Research(IJCER) is an intentional online Journal in English monthly publishing journal. This Journal publish original research work that contributes significantly to further the scientific knowledge in engineering and Technology.
This document presents a new iris segmentation method for iris recognition systems. The proposed method uses Canny edge detection and Hough transform to locate the iris boundary after finding the pupil boundary using image gray levels. Experiments on the CASIA iris image database of 756 images show the method can accurately detect the iris boundary in 99.2% of images. This is an improvement over other existing segmentation techniques. The key steps of the proposed method are preprocessing, segmentation using Canny edge detection and Hough transform, normalization using the rubber sheet model, feature encoding with Gabor wavelets, and matching with Hamming distance.
International Journal of Engineering and Science Invention (IJESI)inventionjournals
International Journal of Engineering and Science Invention (IJESI) is an international journal intended for professionals and researchers in all fields of computer science and electronics. IJESI publishes research articles and reviews within the whole field Engineering Science and Technology, new teaching methods, assessment, validation and the impact of new technologies and it will continue to provide information on the latest trends and developments in this ever-expanding subject. The publications of papers are selected through double peer reviewed to ensure originality, relevance, and readability. The articles published in our journal can be accessed online.
MULTI SCALE ICA BASED IRIS RECOGNITION USING BSIF AND HOG sipij
Iris is a physiological biometric trait, which is unique among all biometric traits to recognize person
effectively. In this paper we propose Multi-scale Independent Component Analysis (ICA) based Iris
Recognition using Binarized Statistical Image Features (BSIF) and Histogram of Gradient orientation
(HOG). The Left and Right portion is extracted from eye images of CASIA V 1.0 database leaving top and
bottom portion of iris. The multi-scale ICA filter sizes of 5X5, 7X7 and 17X17 are used to correlate with
iris template to obtain BSIF. The HOGs are applied on BSIFs to extract initial features. The final feature is
obtained by fusing three HOGs. The Euclidian Distance is used to compare the final feature of database
image with test image final features to compute performance parameters. It is observed that the
performance of the proposed method is better compared to existing methods.
Eye tracking system has played a significant role in many of today’s applications ranging from military
applications to automotive industries and healthcare sectors. In this paper, a novel system for eye tracking and
estimation of its direction of movement is performed. The proposed system is implemented in real time using an
arduino uno microcontroller and a zigbee wireless device. Experimental results show a successful eye tracking and
movement estimation in real time scenario using the proposed hardware interface.
This document reviews various techniques for iris segmentation in iris recognition systems. It discusses integrodifferential operator and Hough transform approaches, as well as the Masek, fuzzy clustering, and pulling and pushing methods. Each approach has advantages and disadvantages. The Masek method achieves circular iris and pupil localization but has lower accuracy and speed. Fuzzy clustering provides better segmentation for non-cooperative iris recognition but requires an extensive search. The pulling and pushing method aims to develop a more accurate and rapid iris segmentation algorithm.
This document provides a survey of iris segmentation algorithms that have been developed. It discusses the importance of accurate iris segmentation to the effectiveness of iris recognition systems. The major existing iris segmentation techniques are Daugman's integro-differential operator method and Wildes' Hough transform-based approach. The document reviews several iris segmentation algorithms from literature and identifies some limitations, including that much work still needs to be done on segmenting black irises accurately.
Iris recognition is a method of biometric identification.
Biometric identification provides automatic recognition of an
individual based on the unique feature of physiological
characteristics or behavioral characteristic. Iris recognition is a
method of recognizing a person by analyzing the iris pattern.
This survey paper covers the different iris recognition techniques
and methods.
A Survey on Retinal Area Detector From Scanning Laser Ophthalmoscope (SLO) Im...IRJET Journal
This document summarizes a survey on methods for automatically detecting the true retinal area from scanning laser ophthalmoscope (SLO) images, which is an important first step for computer-aided diagnosis of retinal diseases. Distinguishing the retinal area from artifacts in SLO images is challenging. The proposed system uses a machine learning approach involving extracting features from super-pixels of the image, selecting important features, and training a classifier to identify the retinal area versus artifacts. This automated detection of the retinal area could help diagnose retinal disorders more efficiently and at scale compared to manual examination methods.
A comparison of multiple wavelet algorithms for iris recognition 2IAEME Publication
The document compares multiple wavelet algorithms for iris recognition, including complex wavelet transform, Gabor wavelets, and discrete wavelet transform. It first provides background on iris recognition and wavelets. It then describes typical iris recognition systems which involve image acquisition, segmentation, normalization, feature extraction, and matching. Next, it discusses complex wavelets, Gabor wavelets, and discrete wavelet transform for feature extraction in iris recognition. Complex wavelets extract phase and amplitude information to accurately describe oscillating functions. Gabor filters model human visual processing and generate phase-coded bit strings for matching. Discrete wavelet transform uses dyadic wavelet scales and positions for efficient analysis. The paper compares these wavelet algorithms for iris image enhancement,
The document describes a multimodal biometric identification system based on iris and fingerprint recognition. It discusses the individual steps of iris and fingerprint recognition including segmentation, feature extraction, and matching. For fingerprint recognition, minutiae points are extracted and matched. For iris recognition, the iris region is segmented from an eye image and normalized before feature extraction. The multimodal system fuses the matching scores from the individual iris and fingerprint recognition at the matching level to improve accuracy by reducing false acceptance and rejection rates compared to unimodal systems. Experimental results on standard databases show the proposed multimodal approach achieves better performance than unimodal biometrics.
The International Journal of Engineering & Science is aimed at providing a platform for researchers, engineers, scientists, or educators to publish their original research results, to exchange new ideas, to disseminate information in innovative designs, engineering experiences and technological skills. It is also the Journal's objective to promote engineering and technology education. All papers submitted to the Journal will be blind peer-reviewed. Only original articles will be published.
A Proposed Framework for Robust Face Identification SystemAhmed Gad
Presentation of IEEE paper "A Proposed Framework for Robust Face Identification System"
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IRJET- Survey of Iris Recognition TechniquesIRJET Journal
This document summarizes several techniques for iris recognition. It begins with an abstract describing iris recognition and its accuracy compared to other biometric traits. It then reviews four iris recognition techniques in the literature:
1. A technique using moment invariants and Euclidean or Mahalanobis distance classifiers that achieved 100% recognition rates.
2. A segmentation algorithm using Daugman's integro differential operator that improved discrimination capabilities over other methods.
3. A pupil localization technique using negative thresholds and neighbors, and iris boundary detection using contrast enhancement and thresholding, achieving accurate segmentation.
4. A technique using Gaussian mixture models, Gabor filter banks, and simulated annealing to generate iris masks and increase recognition rates
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology
Iris segmentation analysis using integro differential operator and hough tran...Nadeer Abu Jraerr
This document presents a study on iris segmentation analysis using the integro-differential operator and Hough transform techniques in biometric systems. The study experiments with two iris segmentation techniques: the integro-differential operator and Hough transform. The Hough transform technique segmented iris images more successfully than the integro-differential operator, achieving a segmentation accuracy of 80.88% compared to 22.06% for the integro-differential operator. The Hough transform also had lower false rejection and recognition error rates. However, it has higher computational complexity than the integro-differential operator. The document concludes that the Hough transform technique resulted in better overall performance than the integro-differential operator for iris segmentation
Corrosion Behaviour of 6061 Al-SiC Composites in KOH MediumEditor IJCATR
The present research work deals with the corrosion behaviour of 6061 Al-15% (vol) SiC(P) composites. The addition of the
reinforcement like SiC to Aluminium has been reported to decrease the corrosion resistance of the matrix due to several reasons, one
of them being galvanic action between the reinforcement and the matrix. In the present work, the corrosion behaviour of 6061 Al-15%
(vol) SiC(P) composites in KOH at different concentration (0.5M, 1M, 1.5M) and different temperature (300C, 350C, 400C, 450C, 500C)
was determined by Tafel extrapolation technique. The inhibition action of 8-Hydroxyquinoline on corrosion behaviour of 6061 Al-
15% (vol) SiC(P) composites in KOH at different concentration of inhibitor (200ppm, 400ppm); different concentration of medium
(0.5M, 1M,1.5M) and different temperature (300C, 350C, 400C, 450C, 500C) was investigated. The results indicate that corrosion rate
of Al-SiC composite in KOH increases as the concentration of medium increases and also as temperature of medium increases. The
results indicate that the inhibitor is moderately effective in inhibiting the corrosion of 6061 Al-15% (vol) SiC(P) composites. As the
inhibitor concentration increases, the corrosion rate decreases. The surface morphology of the metal surface was investigated using
scanning electron microscope (SEM). Activation energy was evaluated using Arrhenius equation, and enthalpy of activation and
entropy of activation values were calculated using transition state equation
Using a Mobile Based Web Service to Search for Missing People – A Case Study ...Editor IJCATR
Being out of touch with a loved one is concerning and not hearing from someone you care about is terrifying. Several cases
of missing people have been reported for many years, where most of the searches turn out unsuccessful. In order to quickly reunite
families and friends with their missing loved ones, a solution for effectively searching for the missing people is presented. In
evaluation of this solution, an F1 score test was simulated using 20 scenarios, out of which an impressive score of 0.72 was attained.
The study concludes that we need to leverage on mobile based technology to device a more efficient method of finding missing
persons more easily and quickly.
Enhanced Quality of Service Based Routing Protocol Using Hybrid Ant Colony Op...Editor IJCATR
The main problem of QoS routing is to setup a multicast hierarchy that may meet particular QoS constraint. In order to reduce the constraints of the earlier work a new improved technique is proposed in this work. In the proposed technique the issue of multi-cast tree is eliminated using clustering based technique. First of all multi-radio and multichannel based clustering is deployed and these cluster head are responsible
for the multicasting. It will diminish the overall energy consumption of nodes and complexity of intelligent algorithms. The path will be evaluated based upon the ant colony optimization. Thus it has produced better results than other techniques.
IRDO: Iris Recognition by fusion of DTCWT and OLBPIJERA Editor
This document proposes a new iris recognition method called IRDO that fuses Dual Tree Complex Wavelet Transform (DTCWT) and Overlapping Local Binary Pattern (OLBP) features. DTCWT is used to extract micro-texture features from the iris, while OLBP enhances the extraction of edge features. Fusing these two methods results in improved matching performance and classification accuracy compared to state-of-the-the-art techniques. The proposed IRDO method achieves higher iris recognition rates as measured by Total Success Rate and Equal Error Rate.
International Journal of Engineering Research and Development (IJERD)IJERD Editor
International Journal of Engineering Research and Development is an international premier peer reviewed open access engineering and technology journal promoting the discovery, innovation, advancement and dissemination of basic and transitional knowledge in engineering, technology and related disciplines.
Biometric Iris Recognition Based on Hybrid Techniqueijsc
This document presents a study on implementing an iris recognition system using a hybrid technique. The system utilizes several image processing and machine learning techniques. It begins with preprocessing the iris image, including capturing, resizing and converting to grayscale. Histogram equalization is then used for enhancement. Two-dimensional discrete wavelet transform (2D DWT) is applied for feature extraction. Various edge detection algorithms including Canny, Prewitt, Roberts and Sobel are used to detect iris boundaries. The features are then stored in a vector for classification. The system is tested on different iris images and analysis shows 2D DWT and Canny edge detection provide adequate results for feature extraction and iris recognition.
International Journal of Computational Engineering Research(IJCER)ijceronline
International Journal of Computational Engineering Research(IJCER) is an intentional online Journal in English monthly publishing journal. This Journal publish original research work that contributes significantly to further the scientific knowledge in engineering and Technology.
This document presents a new iris segmentation method for iris recognition systems. The proposed method uses Canny edge detection and Hough transform to locate the iris boundary after finding the pupil boundary using image gray levels. Experiments on the CASIA iris image database of 756 images show the method can accurately detect the iris boundary in 99.2% of images. This is an improvement over other existing segmentation techniques. The key steps of the proposed method are preprocessing, segmentation using Canny edge detection and Hough transform, normalization using the rubber sheet model, feature encoding with Gabor wavelets, and matching with Hamming distance.
International Journal of Engineering and Science Invention (IJESI)inventionjournals
International Journal of Engineering and Science Invention (IJESI) is an international journal intended for professionals and researchers in all fields of computer science and electronics. IJESI publishes research articles and reviews within the whole field Engineering Science and Technology, new teaching methods, assessment, validation and the impact of new technologies and it will continue to provide information on the latest trends and developments in this ever-expanding subject. The publications of papers are selected through double peer reviewed to ensure originality, relevance, and readability. The articles published in our journal can be accessed online.
MULTI SCALE ICA BASED IRIS RECOGNITION USING BSIF AND HOG sipij
Iris is a physiological biometric trait, which is unique among all biometric traits to recognize person
effectively. In this paper we propose Multi-scale Independent Component Analysis (ICA) based Iris
Recognition using Binarized Statistical Image Features (BSIF) and Histogram of Gradient orientation
(HOG). The Left and Right portion is extracted from eye images of CASIA V 1.0 database leaving top and
bottom portion of iris. The multi-scale ICA filter sizes of 5X5, 7X7 and 17X17 are used to correlate with
iris template to obtain BSIF. The HOGs are applied on BSIFs to extract initial features. The final feature is
obtained by fusing three HOGs. The Euclidian Distance is used to compare the final feature of database
image with test image final features to compute performance parameters. It is observed that the
performance of the proposed method is better compared to existing methods.
Eye tracking system has played a significant role in many of today’s applications ranging from military
applications to automotive industries and healthcare sectors. In this paper, a novel system for eye tracking and
estimation of its direction of movement is performed. The proposed system is implemented in real time using an
arduino uno microcontroller and a zigbee wireless device. Experimental results show a successful eye tracking and
movement estimation in real time scenario using the proposed hardware interface.
This document reviews various techniques for iris segmentation in iris recognition systems. It discusses integrodifferential operator and Hough transform approaches, as well as the Masek, fuzzy clustering, and pulling and pushing methods. Each approach has advantages and disadvantages. The Masek method achieves circular iris and pupil localization but has lower accuracy and speed. Fuzzy clustering provides better segmentation for non-cooperative iris recognition but requires an extensive search. The pulling and pushing method aims to develop a more accurate and rapid iris segmentation algorithm.
This document provides a survey of iris segmentation algorithms that have been developed. It discusses the importance of accurate iris segmentation to the effectiveness of iris recognition systems. The major existing iris segmentation techniques are Daugman's integro-differential operator method and Wildes' Hough transform-based approach. The document reviews several iris segmentation algorithms from literature and identifies some limitations, including that much work still needs to be done on segmenting black irises accurately.
Iris recognition is a method of biometric identification.
Biometric identification provides automatic recognition of an
individual based on the unique feature of physiological
characteristics or behavioral characteristic. Iris recognition is a
method of recognizing a person by analyzing the iris pattern.
This survey paper covers the different iris recognition techniques
and methods.
A Survey on Retinal Area Detector From Scanning Laser Ophthalmoscope (SLO) Im...IRJET Journal
This document summarizes a survey on methods for automatically detecting the true retinal area from scanning laser ophthalmoscope (SLO) images, which is an important first step for computer-aided diagnosis of retinal diseases. Distinguishing the retinal area from artifacts in SLO images is challenging. The proposed system uses a machine learning approach involving extracting features from super-pixels of the image, selecting important features, and training a classifier to identify the retinal area versus artifacts. This automated detection of the retinal area could help diagnose retinal disorders more efficiently and at scale compared to manual examination methods.
A comparison of multiple wavelet algorithms for iris recognition 2IAEME Publication
The document compares multiple wavelet algorithms for iris recognition, including complex wavelet transform, Gabor wavelets, and discrete wavelet transform. It first provides background on iris recognition and wavelets. It then describes typical iris recognition systems which involve image acquisition, segmentation, normalization, feature extraction, and matching. Next, it discusses complex wavelets, Gabor wavelets, and discrete wavelet transform for feature extraction in iris recognition. Complex wavelets extract phase and amplitude information to accurately describe oscillating functions. Gabor filters model human visual processing and generate phase-coded bit strings for matching. Discrete wavelet transform uses dyadic wavelet scales and positions for efficient analysis. The paper compares these wavelet algorithms for iris image enhancement,
The document describes a multimodal biometric identification system based on iris and fingerprint recognition. It discusses the individual steps of iris and fingerprint recognition including segmentation, feature extraction, and matching. For fingerprint recognition, minutiae points are extracted and matched. For iris recognition, the iris region is segmented from an eye image and normalized before feature extraction. The multimodal system fuses the matching scores from the individual iris and fingerprint recognition at the matching level to improve accuracy by reducing false acceptance and rejection rates compared to unimodal systems. Experimental results on standard databases show the proposed multimodal approach achieves better performance than unimodal biometrics.
The International Journal of Engineering & Science is aimed at providing a platform for researchers, engineers, scientists, or educators to publish their original research results, to exchange new ideas, to disseminate information in innovative designs, engineering experiences and technological skills. It is also the Journal's objective to promote engineering and technology education. All papers submitted to the Journal will be blind peer-reviewed. Only original articles will be published.
A Proposed Framework for Robust Face Identification SystemAhmed Gad
Presentation of IEEE paper "A Proposed Framework for Robust Face Identification System"
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IRJET- Survey of Iris Recognition TechniquesIRJET Journal
This document summarizes several techniques for iris recognition. It begins with an abstract describing iris recognition and its accuracy compared to other biometric traits. It then reviews four iris recognition techniques in the literature:
1. A technique using moment invariants and Euclidean or Mahalanobis distance classifiers that achieved 100% recognition rates.
2. A segmentation algorithm using Daugman's integro differential operator that improved discrimination capabilities over other methods.
3. A pupil localization technique using negative thresholds and neighbors, and iris boundary detection using contrast enhancement and thresholding, achieving accurate segmentation.
4. A technique using Gaussian mixture models, Gabor filter banks, and simulated annealing to generate iris masks and increase recognition rates
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology
Iris segmentation analysis using integro differential operator and hough tran...Nadeer Abu Jraerr
This document presents a study on iris segmentation analysis using the integro-differential operator and Hough transform techniques in biometric systems. The study experiments with two iris segmentation techniques: the integro-differential operator and Hough transform. The Hough transform technique segmented iris images more successfully than the integro-differential operator, achieving a segmentation accuracy of 80.88% compared to 22.06% for the integro-differential operator. The Hough transform also had lower false rejection and recognition error rates. However, it has higher computational complexity than the integro-differential operator. The document concludes that the Hough transform technique resulted in better overall performance than the integro-differential operator for iris segmentation
Corrosion Behaviour of 6061 Al-SiC Composites in KOH MediumEditor IJCATR
The present research work deals with the corrosion behaviour of 6061 Al-15% (vol) SiC(P) composites. The addition of the
reinforcement like SiC to Aluminium has been reported to decrease the corrosion resistance of the matrix due to several reasons, one
of them being galvanic action between the reinforcement and the matrix. In the present work, the corrosion behaviour of 6061 Al-15%
(vol) SiC(P) composites in KOH at different concentration (0.5M, 1M, 1.5M) and different temperature (300C, 350C, 400C, 450C, 500C)
was determined by Tafel extrapolation technique. The inhibition action of 8-Hydroxyquinoline on corrosion behaviour of 6061 Al-
15% (vol) SiC(P) composites in KOH at different concentration of inhibitor (200ppm, 400ppm); different concentration of medium
(0.5M, 1M,1.5M) and different temperature (300C, 350C, 400C, 450C, 500C) was investigated. The results indicate that corrosion rate
of Al-SiC composite in KOH increases as the concentration of medium increases and also as temperature of medium increases. The
results indicate that the inhibitor is moderately effective in inhibiting the corrosion of 6061 Al-15% (vol) SiC(P) composites. As the
inhibitor concentration increases, the corrosion rate decreases. The surface morphology of the metal surface was investigated using
scanning electron microscope (SEM). Activation energy was evaluated using Arrhenius equation, and enthalpy of activation and
entropy of activation values were calculated using transition state equation
Using a Mobile Based Web Service to Search for Missing People – A Case Study ...Editor IJCATR
Being out of touch with a loved one is concerning and not hearing from someone you care about is terrifying. Several cases
of missing people have been reported for many years, where most of the searches turn out unsuccessful. In order to quickly reunite
families and friends with their missing loved ones, a solution for effectively searching for the missing people is presented. In
evaluation of this solution, an F1 score test was simulated using 20 scenarios, out of which an impressive score of 0.72 was attained.
The study concludes that we need to leverage on mobile based technology to device a more efficient method of finding missing
persons more easily and quickly.
Enhanced Quality of Service Based Routing Protocol Using Hybrid Ant Colony Op...Editor IJCATR
The main problem of QoS routing is to setup a multicast hierarchy that may meet particular QoS constraint. In order to reduce the constraints of the earlier work a new improved technique is proposed in this work. In the proposed technique the issue of multi-cast tree is eliminated using clustering based technique. First of all multi-radio and multichannel based clustering is deployed and these cluster head are responsible
for the multicasting. It will diminish the overall energy consumption of nodes and complexity of intelligent algorithms. The path will be evaluated based upon the ant colony optimization. Thus it has produced better results than other techniques.
A Survey on Decision Support Systems in Social MediaEditor IJCATR
Web 3.0 is the upcoming phase in web evolution. Web 3.0 will be about “feeding you the information that you want, when you want it” i.e. personalization of the web. In web 3.0 the basic principle is linking, integrating and analyzing data from various data sources into new information streams by means of semantic technology. So, we can say that Web 3.0 comprises of two platforms semantic technologies and social computing environment. Recommender system is a subclass of decision support system. Recommendations in social web are used to personalize the web [20]. Social Tagging System is one type of social media. In this paper we present the survey of various recommendations in Social Tagging Systems (STSs) like tag, item, user and unified recommendations along with semantic web and also discussed about major thrust areas of research in each category.
Holistic Approach for Arabic Word RecognitionEditor IJCATR
Optical Character Recognition (OCR) is one of the important branches. One segmenting words into character is one of the
most challenging steps on OCR. As the results of advances in machine speeds and memory sizes as well as the availability of large
training dataset, researchers currently study Holistic Approach “recognition of a word without segmentation”. This paper describes a
method to recognize off-line handwritten Arabic names. The classification approach is based on Hidden Markov models.. For each
Arabic word many HMM models with different number of states have been trained. The experiments result are encouraging, it also
show that best number of state for each word need careful selection and considerations.
Understanding Working Memory for Improving LearningEditor IJCATR
A web-based working memory (WM) test system is a management system website that allows students to test their ability
and skills in remembering visual patterns. It also enables you to record and store the data for individuals. The system is developed
using HTML, PHP and MySQL as a database system to manage and store the data. The system targets several users: children and
adults who suffer from attention deficit or learning problems. The main objectives for developing the website are to educate the
community on the benefits of performing the working memory test of the activity of the brain and improvements in social skills and
improving poor academic and professional performance, especially in maths and reading comprehension. This study implements a set
of tasks, testing 59 adults aged 18-24 years of age at King Abdul-Aziz University for testing and measuring WM and cognitive
abilities. Results showed tests depended on the age entry by the user. The implications of the test results will help people know their
WM level before ascertaining the appropriate suggestions, and to make the test suit our society.
A Review on Basic Concepts and Important Standards of Power Quality in Power ...Editor IJCATR
This paper deals with the basic of Power quality in power system. In addition basic definition and important concepts was discussed in simple way. This paper also covers the important power quality standards. In addition IEEE, IEC, SEMI and UIE Power quality standards are listed. This paper would be helpful for the UG and PG students to study about the basics of Power quality in electrical engineering.
Photo-Oxygenated Derivatives from EugenolEditor IJCATR
Photo-oxygenation reaction was performed on eugenol (1) (2- methoxy-4-(2'-propenyl) phenol) in chloroform as a solvent and tetraphenyl porphrine (TPP) as singlet oxygen sensitizer. Irradiation of the reaction mixture was carried out by sodium lamp at -20 °C for six hrs., during which dry oxygen was allowed to pass through the reaction mixture. Two hydroperoxides (3) and (4) were formed. Eugenol methyl ether (2) was also photo-oxygenated under the same conditions of eugenol, where only the side chain was photo-oxygenated at position C-1' to give product (5). In addition to the epoxide derivative of eugenol methyl ester (8) was prepared and its reaction with aminoantipyrine was carried out to give product (9). Product (8) could be considered as a DNA- alkylating agent.
Mobile Personalized Notes Using Memory PackageEditor IJCATR
Smart phones and their mobile application have been deeply affected people life in the modern society. We can find many kinds of mobile applications, either in Google Play or Apple Store, designed according to novel motivations to assist us in improving people life. This paper aims to develop a personalized note tool on smart phones to integrate different types of multimedia information to help the users record activities. In this paper we propose a structure called memory package for integrating multimedia information on smart phones. Users can create a memory package in a time period to record their activities by using multimedia contents such as text, image, video, audio, and GPS records. Our system designs a unified interface for the memory package that can help users easily generate and review their packages on phones. Users can preserve clips of user activities of life anytime and anywhere using the proposed system of personalized notes as well as the memory package.
Android and iOS Hybrid Applications for Surabaya Public Transportation RouteEditor IJCATR
This document describes research conducted to develop a hybrid mobile application providing route and transportation information for public buses (called bemos) in Surabaya, Indonesia. The application was created using technologies like PhoneGap to make it compatible with both Android and iOS devices. It allows users to search for routes between locations, see available bemo lines, and get directions and cost estimates. The application was tested on various devices and provided route planning capabilities and maps to help passengers navigate the public transportation system in Surabaya.
LEACH is a hierarchical protocol in which most nodes transmit to cluster heads, and the cluster heads aggregate and
compress the data and forward it to the base station (sink).In LEACH, a TDMA-based MAC protocol is integrated with clustering and
a simple “routing” protocol. The goal of LEACH is to lower the energy consumption required to create and maintain clusters or to use
the energy of the nodes in such a manner so as to improve the life time of a wireless sensor network. In this paper we are presenting an
overview of the different protocol changes made in LEACH to improve network lifetime, throughput, coverage area of network etc.
This document describes the development of a web-based job fair information system using the waterfall model of software development. The system allows users to access information on job vacancies, registration for vacancies, and test schedules. It was developed using requirements collection, specification and design, implementation, and testing phases of the waterfall model. The system provides information to both job seekers and administrators. For job seekers, it allows viewing of information and online registration for vacancies. Administrators can manage all data and information on the system. The system was tested on different browsers and needs further improvement for use on mobile devices.
Photo-Oxygenated Derivatives from EugenolEditor IJCATR
Photo-oxygenation reaction was performed on eugenol (1) (2- methoxy-4-(2'-propenyl) phenol) in
chloroform as a solvent and tetraphenyl porphrine (TPP) as singlet oxygen sensitizer. Irradiation of the reaction
mixture was carried out by sodium lamp at -20 °C for six hrs., during which dry oxygen was allowed to pass
through the reaction mixture. Two hydroperoxides (3) and (4) were formed. Eugenol methyl ether (2) was also
photo-oxygenated under the same conditions of eugenol, where only the side chain was photo-oxygenated at
position C-1' to give product (5). In addition to the epoxide derivative of eugenol methyl ester (8) was prepared
and its reaction with aminoantipyrine was carried out to give product (9). Product (8) could be considered as a
DNA- alkylating agent
Software Architecture Evaluation of Unmanned Aerial Vehicles Fuzzy Based Cont...Editor IJCATR
In this survey paper we discuss the recent techniques for software architecture evaluation methods for Unmanned Aerial Vehicle (UAV) systems that use fuzzy control methodology. We discuss the current methodologies and evaluation approaches, identify their limitations, and discuss the open research issues. These issues include methods used to evaluate the level of risk, communications latency, availability, sensor performance, automation, and human interaction.
Distributed Digital Artifacts on the Semantic WebEditor IJCATR
Distributed digital artifacts incorporate cryptographic hash values to URI called trusty URIs in a distributed environment
building good in quality, verifiable and unchangeable web resources to prevent the rising man in the middle attack. The greatest
challenge of a centralized system is that it gives users no possibility to check whether data have been modified and the communication
is limited to a single server. As a solution for this, is the distributed digital artifact system, where resources are distributed among
different domains to enable inter-domain communication. Due to the emerging developments in web, attacks have increased rapidly,
among which man in the middle attack (MIMA) is a serious issue, where user security is at its threat. This work tries to prevent MIMA
to an extent, by providing self reference and trusty URIs even when presented in a distributed environment. Any manipulation to the
data is efficiently identified and any further access to that data is blocked by informing user that the uniform location has been
changed. System uses self-reference to contain trusty URI for each resource, lineage algorithm for generating seed and SHA-512 hash
generation algorithm to ensure security. It is implemented on the semantic web, which is an extension to the world wide web, using
RDF (Resource Description Framework) to identify the resource. Hence the framework was developed to overcome existing
challenges by making the digital artifacts on the semantic web distributed to enable communication between different domains across
the network securely and thereby preventing MIMA.
Feature Extraction Techniques and Classification Algorithms for EEG Signals t...Editor IJCATR
This document reviews techniques for extracting features and classifying EEG signals to detect human stress levels. It discusses EEG signals and how they can provide information about mental states. It also reviews common feature extraction methods like DCT and DWT that can preprocess EEG data by transforming it from the time to frequency domain. Classification algorithms like KNN, LDA, and Naive Bayes that can classify EEG data are also examined. The document proposes a system to use a Neurosky Mindwave EEG headset to record raw EEG signals, preprocess them with DWT, and classify stress levels using a combination of classifiers.
The document proposes a unified framework for iris recognition that addresses challenges in unconstrained acquisition, robust matching, and privacy. It uses random projections and sparse representations to select good quality iris images, recognize iris patterns in a single step, and introduce cancelable templates for enhanced privacy without compromising security or recognition performance. Experimental results on public datasets demonstrate benefits of the proposed approach for robust and accurate iris recognition.
Biometric Iris Recognition Based on Hybrid Technique ijsc
Iris Recognition is one of the important biometric recognition systems that identify people based on their eyes and iris. In this paper the iris recognition algorithm is implemented via histogram equalization and wavelet techniques. In this paper the iris recognition approach is implemented via many steps, these steps are concentrated on image capturing, enhancement and identification. Different types of edge detection mechanisms; Canny scheme, Prewitt scheme, Roberts scheme and Sobel scheme are used to detect iris boundaries in the eyes digital image. The implemented system gives adequate results via different types of iris images.
Enhance iris segmentation method for person recognition based on image proces...TELKOMNIKA JOURNAL
The limitation of traditional iris recognition systems to process iris images captured in unconstraint environments is a breakthrough. Automatic iris recognition has to face unpredictable variations of iris images in real-world applications. For example, the most challenging problems are related to the severe noise effects that are inherent to these unconstrained iris recognition systems, varying illumination, obstruction of the upper or lower eyelids, the eyelash overlap with the iris region, specular highlights on pupils which come from a spot of light during captured the image, and decentralization of iris image which caused by the person’s gaze. Iris segmentation is one of the most important processes in iris recognition. Due to the different types of noise in the eye image, the segmentation result may be erroneous. To solve this problem, this paper develops an efficient iris segmentation algorithm using image processing techniques. Firstly, the outer boundary segmentation of the iris problem is solved. Then the pupil boundary is detected. Testes are done on the Chinese Academy of Sciences’ Institute of Automation (CASIA) database. Experimental results indicate that the proposed algorithm is efficient and effective in terms of iris segmentation and reduction of time processing. The accuracy results for both datasets (CASIA-V1 and V4) are 100% and 99.16 respectively.
Iris Biometric Based Person Identification Using Deep Learning TechniqueIRJET Journal
This document presents a person identification system based on iris recognition using deep learning. It uses the ResNet-50 model for feature extraction from iris images. The system first preprocesses iris images to remove noise and reflections. It then segments the iris region using Daugman's operator and normalizes it using his rubber sheet model. The normalized iris images are input to the pre-trained ResNet-50 model to extract features. Finally, multiclass SVM is used to perform person identification based on the extracted features. The system was tested on the VISA iris database and achieved 95% accuracy in identification.
A Literature Review on Iris Segmentation Techniques for Iris Recognition SystemsIOSR Journals
This document reviews various techniques for iris segmentation in iris recognition systems. It discusses 8 techniques: (1) Integrodifferential operator, (2) Hough transform, (3) Masek method, (4) Fuzzy clustering algorithm, (5) Pulling and Pushing method, (6) Eight-neighbor connection based clustering, (7) Segmentation approach based on Fourier spectral density, and (8) Circular Gabor Filter. Each technique achieves some level of segmentation accuracy but also has disadvantages like high computational time, low accuracy, or poor performance on noisy images. The document concludes that a unified framework approach provides the highest overall segmentation accuracy for robustly segmenting iris images.
The document discusses using genetic algorithms to optimize iris recognition systems. It evaluates the performance of such a system on two iris databases, CASIA and UBIRIS. For CASIA, the genetic algorithm approach achieved 100% recognition rate and compatibility with all images in the database. For UBIRIS, the recognition rate was 82.6%, with accurate matches found for 124 out of 150 images. The system implemented genetic algorithms to optimize iris feature extraction and matching, improving recognition performance. It provides a concise evaluation of how well genetic algorithms can optimize an iris recognition system using two standard databases.
The document discusses a proposed multimodal biometric system that uses feature-level fusion of fingerprints, face, and eye tracking biometrics. It extracts features from each biometric individually and then uses a joint sparse representation method to fuse the features together while accounting for noise and occlusion. This sparse representation forcing the different biometric features to interact through shared sparse coefficients. The proposed system aims to make multimodal biometrics recognition more robust to problems like noisy data, non-universality of single biometrics, intraclass variations, and spoof attacks.
IRJET - Detection of Skin Cancer using Convolutional Neural NetworkIRJET Journal
This document presents a method for detecting skin cancer using convolutional neural networks. The proposed method involves collecting skin images, preprocessing them by removing noise and segmenting regions of interest, extracting features like asymmetry, border, color, and diameter, performing dimensionality reduction using principal component analysis, calculating dermoscopy scores, and classifying images as malignant or benign using a convolutional neural network (CNN) model. The CNN model achieves 92.5% accuracy in classification. The document provides background on skin cancer and challenges with traditional biopsy methods. It describes the system architecture including data collection, preprocessing, segmentation, feature extraction, and classification steps. Key aspects of CNNs like convolutional, ReLU, pooling, and fully connected layers are also overviewed
A survey paper on various biometric security system methodsIRJET Journal
This document summarizes various biometric security systems for identification. It discusses fingerprint recognition, iris recognition, and face recognition methods. It provides an overview of different approaches that have been proposed, including using watermarking, edge detection techniques, adaptive boosting algorithms, and fuzzy logic. The document also analyzes the drawbacks of previous methods and proposes using a multimodal biometric system that fuses fingerprints, iris, and face for more secure identification. Overall, the document surveys different biometric identification techniques and highlights that a multimodal approach can help overcome limitations of individual methods.
Deep Learning-Based Skin Lesion Detection and Classification: A ReviewIRJET Journal
This document reviews various deep learning techniques for skin lesion detection and classification. It summarizes 10 research papers that detect and segment skin lesions using techniques like convolutional neural networks, fuzzy logic, grabcut algorithm, and adaptive neuro-fuzzy classifiers. The papers achieved good results but had limitations like increased computational time and need for improved segmentation methods. Overall, deep learning has proven effective for skin lesion analysis, but further research is still needed to develop more optimized models.
This document discusses various soft computing techniques for iris recognition, specifically focusing on two neural network approaches: Competitive neural network Learning Vector Quantization (LVQ) and Adaptive Resonance Associative Map (ARAM). It provides an overview of iris recognition as a biometric method, summarizes preprocessing steps like localization, segmentation, and normalization of iris images. It also describes feature extraction and matching steps. Finally, it defines artificial neural networks and discusses how LVQ and ARAM can be used for pattern matching in iris recognition applications.
The document describes a skin cancer detection mobile application that uses image processing and machine learning. The application analyzes skin images for characteristics of melanoma like asymmetry, border, color, diameter and texture. It trains a model using the MobileNet-v2 architecture on datasets containing thousands of images. The trained model achieves 70% accuracy in detecting melanoma and differentiating normal and abnormal skin lesions when tested on new images. The application has potential to help identify skin cancer in early stages and assist medical practitioners.
This document summarizes a research paper on improving the performance of multimodal biometrics using cryptosystems. The paper proposes fusing iris and fingerprint biometrics at the feature level before applying encryption for enhanced security. It discusses extracting features from iris and fingerprint images, fusing the features, and then encrypting the fused template. This approach aims to improve accuracy over unimodal biometrics while enhancing security through encryption. The paper reviews related work on multimodal biometrics and cryptosystems, and presents results showing the proposed approach effectively extracts features and fuses the biometrics for identification.
Performance Enhancement Of Multimodal Biometrics Using CryptosystemIJERA Editor
Multimodal biometrics means the unification of two or more uni modal biometrics so as to make the system more reliable and secure. Such systems promise better security. This study is a blend of iris and fingerprint recognition technique and their fusion at feature level. Our work comprises of two main sections: feature extraction of both modalities and fusing them before matching and finally application of an encryption technique to enhance the security of the fused template.
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Automated attendance system using Face recognitionIRJET Journal
This document describes an automated attendance system using face recognition. The system uses image capture to take photos of students entering the classroom. It then uses the Viola-Jones algorithm for face detection and PCA for feature selection and SVM for classification to recognize students' faces and mark their attendance automatically. When compared to traditional attendance methods, this system saves time and helps monitor students. It discusses related work using RFID, fingerprints, and iris recognition for attendance systems. It outlines the proposed system's modules for image capture, face detection, preprocessing, database development, and postprocessing. Finally, it discusses results, conclusions, and opportunities for future work to improve recognition rates under various conditions.
This document describes an iris recognition system implemented using National Instruments LabVIEW for secure voting. The system has four main stages: 1) image acquisition using an infrared camera, 2) iris localization by detecting circles in the iris image, 3) pattern matching to extract an iris code, and 4) authentication by matching the iris code to a database. The database stores voter information and iris codes in an encrypted format. On voting day, the system matches the voter's ID and captured iris image to the database to verify their identity before allowing them to vote. The system aims to provide more secure identity verification than traditional password or ID systems.
This document summarizes a study on iris recognition. It discusses how iris recognition works by capturing high-resolution images of a person's iris and extracting distinguishing features to create biometric templates for identification. The key steps described are iris localization to isolate the iris region, feature extraction using filters to encode patterns into binary codes, and template matching using Hamming distance to compare templates and identify matches. Advantages of iris recognition include very high accuracy and verification time under 5 seconds. Disadvantages include its intrusive nature and high memory requirements. Applications discussed include security for ATMs, computers, buildings, and airports.
A PROJECT REPORT ON IRIS RECOGNITION SYSTEM USING MATLABMaria Perkins
1. Iris recognition is a reliable biometric authentication method that uses the unique patterns in the iris to identify individuals.
2. Previous work has focused on detecting fake irises using techniques like analyzing image quality features, extracting texture features from the iris, and applying weighted local binary patterns.
3. Detecting fake irises using printed contact lenses is challenging but important for security. Methods have analyzed features like iris edge sharpness, iris-texton histograms, and gray-level co-occurrence matrices to differentiate real and fake irises.
4. Combining local descriptors like SIFT with local binary patterns can improve fake iris detection performance by making the approach
AN EFFICIENT FACE RECOGNITION EMPLOYING SVM AND BU-LDPIRJET Journal
The document presents a study on an efficient face recognition method employing support vector machines (SVM) and biomimetic uncorrelated local difference projection (BU-LDP). The study proposes using BU-LDP, which is based on uncorrelated local projection but uses a different neighborhood coefficient calculation approach inspired by human perception. Experimental results on several datasets show that BU-LDP and its kernel variant KBU-LDP outperform state-of-the-art methods for face recognition. Future work will focus on addressing the "one sample problem" and applying the approach to unlabeled data.
Similar to Evaluation of Iris Recognition System on Multiple Feature Extraction Algorithms and its Combinations (20)
Text Mining in Digital Libraries using OKAPI BM25 ModelEditor IJCATR
The emergence of the internet has made vast amounts of information available and easily accessible online. As a result, most libraries have digitized their content in order to remain relevant to their users and to keep pace with the advancement of the internet. However, these digital libraries have been criticized for using inefficient information retrieval models that do not perform relevance ranking to the retrieved results. This paper proposed the use of OKAPI BM25 model in text mining so as means of improving relevance ranking of digital libraries. Okapi BM25 model was selected because it is a probability-based relevance ranking algorithm. A case study research was conducted and the model design was based on information retrieval processes. The performance of Boolean, vector space, and Okapi BM25 models was compared for data retrieval. Relevant ranked documents were retrieved and displayed at the OPAC framework search page. The results revealed that Okapi BM 25 outperformed Boolean model and Vector Space model. Therefore, this paper proposes the use of Okapi BM25 model to reward terms according to their relative frequencies in a document so as to improve the performance of text mining in digital libraries.
Green Computing, eco trends, climate change, e-waste and eco-friendlyEditor IJCATR
This document discusses green computing practices and sustainable IT services. It provides an overview of factors driving adoption of green computing to reduce costs and environmental impact of data centers, such as rising energy costs and density. Green strategies discussed include improving infrastructure efficiency, power management, thermal management, efficient product design, and virtualization to optimize resource utilization. The document examines how green computing aims to lower costs and environmental footprint, and how sustainable IT services take a broader approach considering economic, environmental and social impacts.
Policies for Green Computing and E-Waste in NigeriaEditor IJCATR
Computers today are an integral part of individuals’ lives all around the world, but unfortunately these devices are toxic to the environment given the materials used, their limited battery life and technological obsolescence. Individuals are concerned about the hazardous materials ever present in computers, even if the importance of various attributes differs, and that a more environment -friendly attitude can be obtained through exposure to educational materials. In this paper, we aim to delineate the problem of e-waste in Nigeria and highlight a series of measures and the advantage they herald for our country and propose a series of action steps to develop in these areas further. It is possible for Nigeria to have an immediate economic stimulus and job creation while moving quickly to abide by the requirements of climate change legislation and energy efficiency directives. The costs of implementing energy efficiency and renewable energy measures are minimal as they are not cash expenditures but rather investments paid back by future, continuous energy savings.
Performance Evaluation of VANETs for Evaluating Node Stability in Dynamic Sce...Editor IJCATR
Vehicular ad hoc networks (VANETs) are a favorable area of exploration which empowers the interconnection amid the movable vehicles and between transportable units (vehicles) and road side units (RSU). In Vehicular Ad Hoc Networks (VANETs), mobile vehicles can be organized into assemblage to promote interconnection links. The assemblage arrangement according to dimensions and geographical extend has serious influence on attribute of interaction .Vehicular ad hoc networks (VANETs) are subclass of mobile Ad-hoc network involving more complex mobility patterns. Because of mobility the topology changes very frequently. This raises a number of technical challenges including the stability of the network .There is a need for assemblage configuration leading to more stable realistic network. The paper provides investigation of various simulation scenarios in which cluster using k-means algorithm are generated and their numbers are varied to find the more stable configuration in real scenario of road.
Optimum Location of DG Units Considering Operation ConditionsEditor IJCATR
The optimal sizing and placement of Distributed Generation units (DG) are becoming very attractive to researchers these days. In this paper a two stage approach has been used for allocation and sizing of DGs in distribution system with time varying load model. The strategic placement of DGs can help in reducing energy losses and improving voltage profile. The proposed work discusses time varying loads that can be useful for selecting the location and optimizing DG operation. The method has the potential to be used for integrating the available DGs by identifying the best locations in a power system. The proposed method has been demonstrated on 9-bus test system.
Analysis of Comparison of Fuzzy Knn, C4.5 Algorithm, and Naïve Bayes Classifi...Editor IJCATR
Early detection of diabetes mellitus (DM) can prevent or inhibit complication. There are several laboratory test that must be done to detect DM. The result of this laboratory test then converted into data training. Data training used in this study generated from UCI Pima Database with 6 attributes that were used to classify positive or negative diabetes. There are various classification methods that are commonly used, and in this study three of them were compared, which were fuzzy KNN, C4.5 algorithm and Naïve Bayes Classifier (NBC) with one identical case. The objective of this study was to create software to classify DM using tested methods and compared the three methods based on accuracy, precision, and recall. The results showed that the best method was Fuzzy KNN with average and maximum accuracy reached 96% and 98%, respectively. In second place, NBC method had respective average and maximum accuracy of 87.5% and 90%. Lastly, C4.5 algorithm had average and maximum accuracy of 79.5% and 86%, respectively.
Web Scraping for Estimating new Record from Source SiteEditor IJCATR
Study in the Competitive field of Intelligent, and studies in the field of Web Scraping, have a symbiotic relationship mutualism. In the information age today, the website serves as a main source. The research focus is on how to get data from websites and how to slow down the intensity of the download. The problem that arises is the website sources are autonomous so that vulnerable changes the structure of the content at any time. The next problem is the system intrusion detection snort installed on the server to detect bot crawler. So the researchers propose the use of the methods of Mining Data Records and the method of Exponential Smoothing so that adaptive to changes in the structure of the content and do a browse or fetch automatically follow the pattern of the occurrences of the news. The results of the tests, with the threshold 0.3 for MDR and similarity threshold score 0.65 for STM, using recall and precision values produce f-measure average 92.6%. While the results of the tests of the exponential estimation smoothing using ? = 0.5 produces MAE 18.2 datarecord duplicate. It slowed down to 3.6 datarecord from 21.8 datarecord results schedule download/fetch fix in an average time of occurrence news.
Evaluating Semantic Similarity between Biomedical Concepts/Classes through S...Editor IJCATR
Most of the existing semantic similarity measures that use ontology structure as their primary source can measure semantic similarity between concepts/classes using single ontology. The ontology-based semantic similarity techniques such as structure-based semantic similarity techniques (Path Length Measure, Wu and Palmer’s Measure, and Leacock and Chodorow’s measure), information content-based similarity techniques (Resnik’s measure, Lin’s measure), and biomedical domain ontology techniques (Al-Mubaid and Nguyen’s measure (SimDist)) were evaluated relative to human experts’ ratings, and compared on sets of concepts using the ICD-10 “V1.0” terminology within the UMLS. The experimental results validate the efficiency of the SemDist technique in single ontology, and demonstrate that SemDist semantic similarity techniques, compared with the existing techniques, gives the best overall results of correlation with experts’ ratings.
Semantic Similarity Measures between Terms in the Biomedical Domain within f...Editor IJCATR
The techniques and tests are tools used to define how measure the goodness of ontology or its resources. The similarity between biomedical classes/concepts is an important task for the biomedical information extraction and knowledge discovery. However, most of the semantic similarity techniques can be adopted to be used in the biomedical domain (UMLS). Many experiments have been conducted to check the applicability of these measures. In this paper, we investigate to measure semantic similarity between two terms within single ontology or multiple ontologies in ICD-10 “V1.0” as primary source, and compare my results to human experts score by correlation coefficient.
A Strategy for Improving the Performance of Small Files in Openstack Swift Editor IJCATR
This is an effective way to improve the storage access performance of small files in Openstack Swift by adding an aggregate storage module. Because Swift will lead to too much disk operation when querying metadata, the transfer performance of plenty of small files is low. In this paper, we propose an aggregated storage strategy (ASS), and implement it in Swift. ASS comprises two parts which include merge storage and index storage. At the first stage, ASS arranges the write request queue in chronological order, and then stores objects in volumes. These volumes are large files that are stored in Swift actually. During the short encounter time, the object-to-volume mapping information is stored in Key-Value store at the second stage. The experimental results show that the ASS can effectively improve Swift's small file transfer performance.
Integrated System for Vehicle Clearance and RegistrationEditor IJCATR
Efficient management and control of government's cash resources rely on government banking arrangements. Nigeria, like many low income countries, employed fragmented systems in handling government receipts and payments. Later in 2016, Nigeria implemented a unified structure as recommended by the IMF, where all government funds are collected in one account would reduce borrowing costs, extend credit and improve government's fiscal policy among other benefits to government. This situation motivated us to embark on this research to design and implement an integrated system for vehicle clearance and registration. This system complies with the new Treasury Single Account policy to enable proper interaction and collaboration among five different level agencies (NCS, FRSC, SBIR, VIO and NPF) saddled with vehicular administration and activities in Nigeria. Since the system is web based, Object Oriented Hypermedia Design Methodology (OOHDM) is used. Tools such as Php, JavaScript, css, html, AJAX and other web development technologies were used. The result is a web based system that gives proper information about a vehicle starting from the exact date of importation to registration and renewal of licensing. Vehicle owner information, custom duty information, plate number registration details, etc. will also be efficiently retrieved from the system by any of the agencies without contacting the other agency at any point in time. Also number plate will no longer be the only means of vehicle identification as it is presently the case in Nigeria, because the unified system will automatically generate and assigned a Unique Vehicle Identification Pin Number (UVIPN) on payment of duty in the system to the vehicle and the UVIPN will be linked to the various agencies in the management information system.
Assessment of the Efficiency of Customer Order Management System: A Case Stu...Editor IJCATR
The Supermarket Management System deals with the automation of buying and selling of good and services. It includes both sales and purchase of items. The project Supermarket Management System is to be developed with the objective of making the system reliable, easier, fast, and more informative.
Energy-Aware Routing in Wireless Sensor Network Using Modified Bi-Directional A*Editor IJCATR
Energy is a key component in the Wireless Sensor Network (WSN)[1]. The system will not be able to run according to its function without the availability of adequate power units. One of the characteristics of wireless sensor network is Limitation energy[2]. A lot of research has been done to develop strategies to overcome this problem. One of them is clustering technique. The popular clustering technique is Low Energy Adaptive Clustering Hierarchy (LEACH)[3]. In LEACH, clustering techniques are used to determine Cluster Head (CH), which will then be assigned to forward packets to Base Station (BS). In this research, we propose other clustering techniques, which utilize the Social Network Analysis approach theory of Betweeness Centrality (BC) which will then be implemented in the Setup phase. While in the Steady-State phase, one of the heuristic searching algorithms, Modified Bi-Directional A* (MBDA *) is implemented. The experiment was performed deploy 100 nodes statically in the 100x100 area, with one Base Station at coordinates (50,50). To find out the reliability of the system, the experiment to do in 5000 rounds. The performance of the designed routing protocol strategy will be tested based on network lifetime, throughput, and residual energy. The results show that BC-MBDA * is better than LEACH. This is influenced by the ways of working LEACH in determining the CH that is dynamic, which is always changing in every data transmission process. This will result in the use of energy, because they always doing any computation to determine CH in every transmission process. In contrast to BC-MBDA *, CH is statically determined, so it can decrease energy usage.
Security in Software Defined Networks (SDN): Challenges and Research Opportun...Editor IJCATR
In networks, the rapidly changing traffic patterns of search engines, Internet of Things (IoT) devices, Big Data and data centers has thrown up new challenges for legacy; existing networks; and prompted the need for a more intelligent and innovative way to dynamically manage traffic and allocate limited network resources. Software Defined Network (SDN) which decouples the control plane from the data plane through network vitalizations aims to address these challenges. This paper has explored the SDN architecture and its implementation with the OpenFlow protocol. It has also assessed some of its benefits over traditional network architectures, security concerns and how it can be addressed in future research and related works in emerging economies such as Nigeria.
Measure the Similarity of Complaint Document Using Cosine Similarity Based on...Editor IJCATR
Report handling on "LAPOR!" (Laporan, Aspirasi dan Pengaduan Online Rakyat) system depending on the system administrator who manually reads every incoming report [3]. Read manually can lead to errors in handling complaints [4] if the data flow is huge and grows rapidly, it needs at least three days to prepare a confirmation and it sensitive to inconsistencies [3]. In this study, the authors propose a model that can measure the identities of the Query (Incoming) with Document (Archive). The authors employed Class-Based Indexing term weighting scheme, and Cosine Similarities to analyse document similarities. CoSimTFIDF, CoSimTFICF and CoSimTFIDFICF values used in classification as feature for K-Nearest Neighbour (K-NN) classifier. The optimum result evaluation is pre-processing employ 75% of training data ratio and 25% of test data with CoSimTFIDF feature. It deliver a high accuracy 84%. The k = 5 value obtain high accuracy 84.12%
Hangul Recognition Using Support Vector MachineEditor IJCATR
The recognition of Hangul Image is more difficult compared with that of Latin. It could be recognized from the structural arrangement. Hangul is arranged from two dimensions while Latin is only from the left to the right. The current research creates a system to convert Hangul image into Latin text in order to use it as a learning material on reading Hangul. In general, image recognition system is divided into three steps. The first step is preprocessing, which includes binarization, segmentation through connected component-labeling method, and thinning with Zhang Suen to decrease some pattern information. The second is receiving the feature from every single image, whose identification process is done through chain code method. The third is recognizing the process using Support Vector Machine (SVM) with some kernels. It works through letter image and Hangul word recognition. It consists of 34 letters, each of which has 15 different patterns. The whole patterns are 510, divided into 3 data scenarios. The highest result achieved is 94,7% using SVM kernel polynomial and radial basis function. The level of recognition result is influenced by many trained data. Whilst the recognition process of Hangul word applies to the type 2 Hangul word with 6 different patterns. The difference of these patterns appears from the change of the font type. The chosen fonts for data training are such as Batang, Dotum, Gaeul, Gulim, Malgun Gothic. Arial Unicode MS is used to test the data. The lowest accuracy is achieved through the use of SVM kernel radial basis function, which is 69%. The same result, 72 %, is given by the SVM kernel linear and polynomial.
Application of 3D Printing in EducationEditor IJCATR
This paper provides a review of literature concerning the application of 3D printing in the education system. The review identifies that 3D Printing is being applied across the Educational levels [1] as well as in Libraries, Laboratories, and Distance education systems. The review also finds that 3D Printing is being used to teach both students and trainers about 3D Printing and to develop 3D Printing skills.
Survey on Energy-Efficient Routing Algorithms for Underwater Wireless Sensor ...Editor IJCATR
In underwater environment, for retrieval of information the routing mechanism is used. In routing mechanism there are three to four types of nodes are used, one is sink node which is deployed on the water surface and can collect the information, courier/super/AUV or dolphin powerful nodes are deployed in the middle of the water for forwarding the packets, ordinary nodes are also forwarder nodes which can be deployed from bottom to surface of the water and source nodes are deployed at the seabed which can extract the valuable information from the bottom of the sea. In underwater environment the battery power of the nodes is limited and that power can be enhanced through better selection of the routing algorithm. This paper focuses the energy-efficient routing algorithms for their routing mechanisms to prolong the battery power of the nodes. This paper also focuses the performance analysis of the energy-efficient algorithms under which we can examine the better performance of the route selection mechanism which can prolong the battery power of the node
Comparative analysis on Void Node Removal Routing algorithms for Underwater W...Editor IJCATR
The designing of routing algorithms faces many challenges in underwater environment like: propagation delay, acoustic channel behaviour, limited bandwidth, high bit error rate, limited battery power, underwater pressure, node mobility, localization 3D deployment, and underwater obstacles (voids). This paper focuses the underwater voids which affects the overall performance of the entire network. The majority of the researchers have used the better approaches for removal of voids through alternate path selection mechanism but still research needs improvement. This paper also focuses the architecture and its operation through merits and demerits of the existing algorithms. This research article further focuses the analytical method of the performance analysis of existing algorithms through which we found the better approach for removal of voids
Decay Property for Solutions to Plate Type Equations with Variable CoefficientsEditor IJCATR
In this paper we consider the initial value problem for a plate type equation with variable coefficients and memory in
1 n R n ), which is of regularity-loss property. By using spectrally resolution, we study the pointwise estimates in the spectral
space of the fundamental solution to the corresponding linear problem. Appealing to this pointwise estimates, we obtain the global
existence and the decay estimates of solutions to the semilinear problem by employing the fixed point theorem
Taking AI to the Next Level in Manufacturing.pdfssuserfac0301
Read Taking AI to the Next Level in Manufacturing to gain insights on AI adoption in the manufacturing industry, such as:
1. How quickly AI is being implemented in manufacturing.
2. Which barriers stand in the way of AI adoption.
3. How data quality and governance form the backbone of AI.
4. Organizational processes and structures that may inhibit effective AI adoption.
6. Ideas and approaches to help build your organization's AI strategy.
zkStudyClub - LatticeFold: A Lattice-based Folding Scheme and its Application...Alex Pruden
Folding is a recent technique for building efficient recursive SNARKs. Several elegant folding protocols have been proposed, such as Nova, Supernova, Hypernova, Protostar, and others. However, all of them rely on an additively homomorphic commitment scheme based on discrete log, and are therefore not post-quantum secure. In this work we present LatticeFold, the first lattice-based folding protocol based on the Module SIS problem. This folding protocol naturally leads to an efficient recursive lattice-based SNARK and an efficient PCD scheme. LatticeFold supports folding low-degree relations, such as R1CS, as well as high-degree relations, such as CCS. The key challenge is to construct a secure folding protocol that works with the Ajtai commitment scheme. The difficulty, is ensuring that extracted witnesses are low norm through many rounds of folding. We present a novel technique using the sumcheck protocol to ensure that extracted witnesses are always low norm no matter how many rounds of folding are used. Our evaluation of the final proof system suggests that it is as performant as Hypernova, while providing post-quantum security.
Paper Link: https://eprint.iacr.org/2024/257
HCL Notes and Domino License Cost Reduction in the World of DLAUpanagenda
Webinar Recording: https://www.panagenda.com/webinars/hcl-notes-and-domino-license-cost-reduction-in-the-world-of-dlau/
The introduction of DLAU and the CCB & CCX licensing model caused quite a stir in the HCL community. As a Notes and Domino customer, you may have faced challenges with unexpected user counts and license costs. You probably have questions on how this new licensing approach works and how to benefit from it. Most importantly, you likely have budget constraints and want to save money where possible. Don’t worry, we can help with all of this!
We’ll show you how to fix common misconfigurations that cause higher-than-expected user counts, and how to identify accounts which you can deactivate to save money. There are also frequent patterns that can cause unnecessary cost, like using a person document instead of a mail-in for shared mailboxes. We’ll provide examples and solutions for those as well. And naturally we’ll explain the new licensing model.
Join HCL Ambassador Marc Thomas in this webinar with a special guest appearance from Franz Walder. It will give you the tools and know-how to stay on top of what is going on with Domino licensing. You will be able lower your cost through an optimized configuration and keep it low going forward.
These topics will be covered
- Reducing license cost by finding and fixing misconfigurations and superfluous accounts
- How do CCB and CCX licenses really work?
- Understanding the DLAU tool and how to best utilize it
- Tips for common problem areas, like team mailboxes, functional/test users, etc
- Practical examples and best practices to implement right away
GraphRAG for Life Science to increase LLM accuracyTomaz Bratanic
GraphRAG for life science domain, where you retriever information from biomedical knowledge graphs using LLMs to increase the accuracy and performance of generated answers
This presentation provides valuable insights into effective cost-saving techniques on AWS. Learn how to optimize your AWS resources by rightsizing, increasing elasticity, picking the right storage class, and choosing the best pricing model. Additionally, discover essential governance mechanisms to ensure continuous cost efficiency. Whether you are new to AWS or an experienced user, this presentation provides clear and practical tips to help you reduce your cloud costs and get the most out of your budget.
Programming Foundation Models with DSPy - Meetup SlidesZilliz
Prompting language models is hard, while programming language models is easy. In this talk, I will discuss the state-of-the-art framework DSPy for programming foundation models with its powerful optimizers and runtime constraint system.
Your One-Stop Shop for Python Success: Top 10 US Python Development Providersakankshawande
Simplify your search for a reliable Python development partner! This list presents the top 10 trusted US providers offering comprehensive Python development services, ensuring your project's success from conception to completion.
Let's Integrate MuleSoft RPA, COMPOSER, APM with AWS IDP along with Slackshyamraj55
Discover the seamless integration of RPA (Robotic Process Automation), COMPOSER, and APM with AWS IDP enhanced with Slack notifications. Explore how these technologies converge to streamline workflows, optimize performance, and ensure secure access, all while leveraging the power of AWS IDP and real-time communication via Slack notifications.
Skybuffer SAM4U tool for SAP license adoptionTatiana Kojar
Manage and optimize your license adoption and consumption with SAM4U, an SAP free customer software asset management tool.
SAM4U, an SAP complimentary software asset management tool for customers, delivers a detailed and well-structured overview of license inventory and usage with a user-friendly interface. We offer a hosted, cost-effective, and performance-optimized SAM4U setup in the Skybuffer Cloud environment. You retain ownership of the system and data, while we manage the ABAP 7.58 infrastructure, ensuring fixed Total Cost of Ownership (TCO) and exceptional services through the SAP Fiori interface.
FREE A4 Cyber Security Awareness Posters-Social Engineering part 3Data Hops
Free A4 downloadable and printable Cyber Security, Social Engineering Safety and security Training Posters . Promote security awareness in the home or workplace. Lock them Out From training providers datahops.com
Salesforce Integration for Bonterra Impact Management (fka Social Solutions A...Jeffrey Haguewood
Sidekick Solutions uses Bonterra Impact Management (fka Social Solutions Apricot) and automation solutions to integrate data for business workflows.
We believe integration and automation are essential to user experience and the promise of efficient work through technology. Automation is the critical ingredient to realizing that full vision. We develop integration products and services for Bonterra Case Management software to support the deployment of automations for a variety of use cases.
This video focuses on integration of Salesforce with Bonterra Impact Management.
Interested in deploying an integration with Salesforce for Bonterra Impact Management? Contact us at sales@sidekicksolutionsllc.com to discuss next steps.
Monitoring and Managing Anomaly Detection on OpenShift.pdfTosin Akinosho
Monitoring and Managing Anomaly Detection on OpenShift
Overview
Dive into the world of anomaly detection on edge devices with our comprehensive hands-on tutorial. This SlideShare presentation will guide you through the entire process, from data collection and model training to edge deployment and real-time monitoring. Perfect for those looking to implement robust anomaly detection systems on resource-constrained IoT/edge devices.
Key Topics Covered
1. Introduction to Anomaly Detection
- Understand the fundamentals of anomaly detection and its importance in identifying unusual behavior or failures in systems.
2. Understanding Edge (IoT)
- Learn about edge computing and IoT, and how they enable real-time data processing and decision-making at the source.
3. What is ArgoCD?
- Discover ArgoCD, a declarative, GitOps continuous delivery tool for Kubernetes, and its role in deploying applications on edge devices.
4. Deployment Using ArgoCD for Edge Devices
- Step-by-step guide on deploying anomaly detection models on edge devices using ArgoCD.
5. Introduction to Apache Kafka and S3
- Explore Apache Kafka for real-time data streaming and Amazon S3 for scalable storage solutions.
6. Viewing Kafka Messages in the Data Lake
- Learn how to view and analyze Kafka messages stored in a data lake for better insights.
7. What is Prometheus?
- Get to know Prometheus, an open-source monitoring and alerting toolkit, and its application in monitoring edge devices.
8. Monitoring Application Metrics with Prometheus
- Detailed instructions on setting up Prometheus to monitor the performance and health of your anomaly detection system.
9. What is Camel K?
- Introduction to Camel K, a lightweight integration framework built on Apache Camel, designed for Kubernetes.
10. Configuring Camel K Integrations for Data Pipelines
- Learn how to configure Camel K for seamless data pipeline integrations in your anomaly detection workflow.
11. What is a Jupyter Notebook?
- Overview of Jupyter Notebooks, an open-source web application for creating and sharing documents with live code, equations, visualizations, and narrative text.
12. Jupyter Notebooks with Code Examples
- Hands-on examples and code snippets in Jupyter Notebooks to help you implement and test anomaly detection models.
How to Interpret Trends in the Kalyan Rajdhani Mix Chart.pdfChart Kalyan
A Mix Chart displays historical data of numbers in a graphical or tabular form. The Kalyan Rajdhani Mix Chart specifically shows the results of a sequence of numbers over different periods.
Introduction of Cybersecurity with OSS at Code Europe 2024Hiroshi SHIBATA
I develop the Ruby programming language, RubyGems, and Bundler, which are package managers for Ruby. Today, I will introduce how to enhance the security of your application using open-source software (OSS) examples from Ruby and RubyGems.
The first topic is CVE (Common Vulnerabilities and Exposures). I have published CVEs many times. But what exactly is a CVE? I'll provide a basic understanding of CVEs and explain how to detect and handle vulnerabilities in OSS.
Next, let's discuss package managers. Package managers play a critical role in the OSS ecosystem. I'll explain how to manage library dependencies in your application.
I'll share insights into how the Ruby and RubyGems core team works to keep our ecosystem safe. By the end of this talk, you'll have a better understanding of how to safeguard your code.
5th LF Energy Power Grid Model Meet-up SlidesDanBrown980551
5th Power Grid Model Meet-up
It is with great pleasure that we extend to you an invitation to the 5th Power Grid Model Meet-up, scheduled for 6th June 2024. This event will adopt a hybrid format, allowing participants to join us either through an online Mircosoft Teams session or in person at TU/e located at Den Dolech 2, Eindhoven, Netherlands. The meet-up will be hosted by Eindhoven University of Technology (TU/e), a research university specializing in engineering science & technology.
Power Grid Model
The global energy transition is placing new and unprecedented demands on Distribution System Operators (DSOs). Alongside upgrades to grid capacity, processes such as digitization, capacity optimization, and congestion management are becoming vital for delivering reliable services.
Power Grid Model is an open source project from Linux Foundation Energy and provides a calculation engine that is increasingly essential for DSOs. It offers a standards-based foundation enabling real-time power systems analysis, simulations of electrical power grids, and sophisticated what-if analysis. In addition, it enables in-depth studies and analysis of the electrical power grid’s behavior and performance. This comprehensive model incorporates essential factors such as power generation capacity, electrical losses, voltage levels, power flows, and system stability.
Power Grid Model is currently being applied in a wide variety of use cases, including grid planning, expansion, reliability, and congestion studies. It can also help in analyzing the impact of renewable energy integration, assessing the effects of disturbances or faults, and developing strategies for grid control and optimization.
What to expect
For the upcoming meetup we are organizing, we have an exciting lineup of activities planned:
-Insightful presentations covering two practical applications of the Power Grid Model.
-An update on the latest advancements in Power Grid -Model technology during the first and second quarters of 2024.
-An interactive brainstorming session to discuss and propose new feature requests.
-An opportunity to connect with fellow Power Grid Model enthusiasts and users.
Driving Business Innovation: Latest Generative AI Advancements & Success StorySafe Software
Are you ready to revolutionize how you handle data? Join us for a webinar where we’ll bring you up to speed with the latest advancements in Generative AI technology and discover how leveraging FME with tools from giants like Google Gemini, Amazon, and Microsoft OpenAI can supercharge your workflow efficiency.
During the hour, we’ll take you through:
Guest Speaker Segment with Hannah Barrington: Dive into the world of dynamic real estate marketing with Hannah, the Marketing Manager at Workspace Group. Hear firsthand how their team generates engaging descriptions for thousands of office units by integrating diverse data sources—from PDF floorplans to web pages—using FME transformers, like OpenAIVisionConnector and AnthropicVisionConnector. This use case will show you how GenAI can streamline content creation for marketing across the board.
Ollama Use Case: Learn how Scenario Specialist Dmitri Bagh has utilized Ollama within FME to input data, create custom models, and enhance security protocols. This segment will include demos to illustrate the full capabilities of FME in AI-driven processes.
Custom AI Models: Discover how to leverage FME to build personalized AI models using your data. Whether it’s populating a model with local data for added security or integrating public AI tools, find out how FME facilitates a versatile and secure approach to AI.
We’ll wrap up with a live Q&A session where you can engage with our experts on your specific use cases, and learn more about optimizing your data workflows with AI.
This webinar is ideal for professionals seeking to harness the power of AI within their data management systems while ensuring high levels of customization and security. Whether you're a novice or an expert, gain actionable insights and strategies to elevate your data processes. Join us to see how FME and AI can revolutionize how you work with data!
Driving Business Innovation: Latest Generative AI Advancements & Success Story
Evaluation of Iris Recognition System on Multiple Feature Extraction Algorithms and its Combinations
1. International Journal of Computer Applications Technology and Research
Volume 4– Issue 8, 592 - 598, 2015, ISSN: 2319–8656
www.ijcat.com 592
Evaluation of Iris Recognition System on Multiple
Feature Extraction Algorithms and its
Combinations
Ashwini M B
Department of
Computer Science,
MMK & SDM Mahila
Maha Vidyalaya, K M
Puram, Mysore,
Karnataka, India
Mohammad Imran
Department of CCSIT,
King Faisal University
Al Ahsa, KSA
Fawaz Alsaade
Department of CCSIT,
King Faisal University
Al Ahsa, KSA
Abstract: Multi-algorithmic approach to enhancing the accuracy of iris recognition system is proposed and
investigated. In this system, features are extracted from the iris using various feature extraction algorithms,
namely LPQ, LBP, Gabor Filter, Haar, Db8 and Db16. Based on the experimental results, it is demonstrated
that Mutli-algorithms Iris Recognition System is performing better than the unimodal system. The accuracy
improvement offered by the proposed approach also showed that using more than two feature extraction
algorithms in extracting the iris system might decrease the system performance. This is due to redundant
features. The paper presents a detailed description of the experiments and provides an analysis of the
performance of the proposed method.
Keywods: Biometrics, Iris, Unimodal, Multiple Algorithms, Feature Level Fusion, Performance of
Algorithms
1. INTRODUCTION
Biometrics is the science of recognizing a person
on the basis of physical or behavioral
characteristics. Psychological characteristics are
characteristics that are gathered or learned during
time (e. g. signature, gait, typing dynamics, voice
features etc.). Physical characteristics are
characteristics that are genetically implied and
possibly influenced by the environment (e. g.
face, iris, retina, finger, vascular structure etc.).
Iris biometric is employed in this work because
of its distinctive and uniqueness in each person
including identical twins and each eye. There are
number of properties that enhance the suitability
of the iris for use in automatic identification. One
important feature is that the iris is inherently
isolated and protected from the external
environment. Moreover, being an internal organ
of the eye, behind the cornea and the aqueous
humor; it is almost impossible to surgically
modify the iris without unacceptable risk of
damage. Also, its physiological response to light
provides a natural test against fake irises [11].
Iris provides many interlacing minute
characteristics such as freckles, coronas, stripes,
furrows, crypts and so on. It is essentially stable
over a person’s life. Iris-based personal
identification systems are noninvasive to their
users. The technology of Iris recognition has
some advantages and disadvantages which make
it appropriate to use in some application and not
2. International Journal of Computer Applications Technology and Research
Volume 4– Issue 8, 592 - 598, 2015, ISSN: 2319–8656
www.ijcat.com 593
to other applications[12]. Some of the
advantages of iris biometrics are as follows: a)
Iris is very accurate biometric. It has low false
acceptance rate, which is important in security
aspect. Therefore iris might be a good biometric
for identification applications. b) The sensing of
the biometric is without physical contact and it is
convenient for the users because the iris pattern
acquisition process uses unnoticeable and distant
cameras. c)Iris recognition system has low cost
training. d) Iris technology has received little
negative press and so is more generally accepted
biometric identifier[2].
There are various unimodal iris recognition
systems exists in real world, unimodal system
means rely on single source of information for
verification/identification. However,
Multibiometric system relies on the evidence
presented by multiple sources of biometric
information. Based on the nature of these
sources, a Multibiometric system can be
classified into one of the following six categories:
multi-sensor, multi-algorithm, multi-instance,
multi-sample, multimodal and hybrid systems [ ].
In some cases, invoking multiple feature
extraction and/or matching algorithms on the
same biometric data can result in improved
matching performance. Multi-algorithm system
consolidates the output of multiple feature
extraction algorithms, or that of multiple
matchers operating on the same feature set. These
systems do not necessitate the deployment of new
sensors and, hence, are cost-effective compared
to other types of multibiometric systems. On the
other hand, the introduction of new feature
extraction and matching modules can increase the
computational complexity of these systems [3].
The work presented in this paper aims to
enhancing the security of iris recognition system
using multi-algorithmic approach. This is
achieved by fusing the data acquired at the
feature level and applying the K-Nearest
Neighbor classifier(K-NN). The rest of the paper
is structured as follows. Section 2 presents related
works. Section 3 introduces the proposed
approach for multi-algorithm iris recognition
system. Section 4 describes the experimental
investigations, and the overall conclusions are
presented in Section 5.
2. RELATED WORKS
Karen et al [1] states that, genetically identical
irises have texture similarity that is not detected
by iris biometrics. By performing experimental
studies on left and right irises of the same
person, it results that are as different as irises of
unrelated people. Similarly, in terms of iris
biometric matching, the eyes of identical twins
are as different as irises of unrelated people. The
experiments done based on texture feature
extraction methods, this highlight the difference
between automated biometric technology and
human viewers. This work suggests that human
examination of pairs of iris images for forensic
purposes may be feasible and results of
experiments suggest that development of
different approaches to automated iris image
analysis could be used to improve current iris
biometric technology. Vijaya et al [4] states that
generally algorithm is divided into four steps,
such as. localization, Normalization, Feature
Extraction and Matching. Doughman‘s approach
is there with highest accuracy of 99.9% and
Kaushik Rai‘s approach is also promising in state
of the art, only thing that can be done is to
decrease the computational time and number of
features to obtain the same efficiency.
Libor et al [5] presents an automatic
segmentation algorithm that remove iris region
from an eye image and isolate eyelid, eyelash and
reflection areas. The iris region was normalized
into a rectangular block with constant dimensions
to account for imaging inconsistencies. However,
the phase data from 1D Log-Gabor filters was
extracted and quantized to four levels to encode
the unique pattern of the iris into a bit-wise
biometric template. The Hamming distance was
employed for classification of iris templates, and
two templates were found to match if a test of
statistical independence was failed. The system
performed with perfect recognition on a set of 75
eye images; however, tests on another set of 624
images resulted in false accept and false reject
rates of 0.005% and 0.238% respectively.
Therefore, iris recognition is shown to be a
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reliable and accurate biometric technology.
Somnath et al [6] present a novel and efficient
approach to extract iris features and matching
technique to compare iris features. This approach
uses Daubechies wavelet transform with four
coefficients. Daubechies wavelet transform is
easy to compute and fast compared to the other
methods on texture analysis. Further, Daubechies
wavelet transform allows to keep the count of
feature vectors into a significantly lesser
numbers.
Fenghua et al [7] presents a multi-algorithmic
fusion approach for iris recognition, which
combines phase based algorithm and zero-
crossing based algorithm. The two algorithms are
fused at the matching score level using SVM
fusion strategy. The experimental results on
CASIA and UBIRIS iris database show that the
proposed approach can improve the recognition
performance compared with the individual
recognition algorithm and SVM based fusion
strategy can give the better performance than the
traditional fusion strategies.
3. METHODS AND MATERIALS
In this section, we emphasis on different iris
recognition methods which are explored in state
of the art approaches. Brief details of different
iris biometric technology methods as well as
feature extraction algorithms are explored here.
3.1 Iris Recognition Methods
a. Phase-based method: It recognizes iris
patterns based on phase information which
is independent of image contrast and
illumination. The first complete,
commercially available phase-based iris
recognition system was designed and
patented in 1994 by J.Daugman [15].
b. Texture-analysis based method: Wildes
proposed iris recognition based on texture
analysis. High quality iris images were
captured using silicon intensified target
camera coupled with a standard frame
grabber and resolution of 512x480
pixels[12].
c. Zero-Crossing representation method: This
method was developed by Boles. It
represents features of the iris at different
resolution levels based on the wavelet
transform zero-crossing. The algorithm is
translation, rotation and scale invariant. The
input images are processed to obtain a set of
1D signals and its zero crossing
representation based on its dyadic wavelet
transform[9].
d. Intensity variations: An Iris recognition
system developed by Li Ma and
characterized by local intensity variations.
The sharp variation points of iris patterns are
recorded as features[9].
e. Independent Component Analysis: The iris
recognition system developed by Ya-Ping
Huang adopts Independent Component
Analysis (ICA) to extract iris texture
features[11].
f. Iris authentication based on Continuous
Dynamic Programming: The technique
proposed by Radhika authenticates iris
based on kinematic characteristics,
acceleration. Pupil extraction begins by
identifying the highest peak from the
histogram which provides the threshold for
lower intensity values of the eye image [12].
3.2 Feature extraction algorithms
In this paper, five different feature extraction
algorithms have been used to extract the features
prior to feature level fusion for the iris biometric.
These are:
a) Local Binary Pattern (LBP)
Local Binary Pattern is an efficient method
used for feature extraction and texture
classification. LBP was first introduced by
Ojala[8]. The LBP operator was introduced as a
complementary measure for local image contrast,
and it was developed as a grayscale invariant
pattern measure adding complementary
information to the “amount” of texture in images.
LBP is ideally suited for applications requiring
fast feature extraction and texture
classification[13]. Due to its discriminative
power and computational simplicity, the LBP
texture operator has become a popular approach
in various applications, including visual
inspection, image retrieval, remote sensing,
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biomedical image analysis, motion analysis,
environmental modeling, and outdoor scene
analysis[3] .
b) Local Phase
Quantization(LPQ)
Ojansivu et al. [8] proposed a new descriptor
for texture classification named as Local phase
quantization (LPQ) that is robust to image
blurring. The descriptor utilizes phase
information computed locally in a window for
every image position. The phases of the four low-
frequency coefficients are computed. These
coefficients are decorrelated and uniformly
quantized in an eight-dimensional space. The
LPQ is in frequency domain, which contained
partial contrast information of the image.
However that is not enough to describe the
texture features without contrast information in
spatial domain. In LPQ algorithm, it firstly
transformed the image from spatial domain to
frequency domain to find the phase information
coefficient for every single point from the image.
Then the covariance between the adjacent pixels
is computed.
c) Haar Wavelet
Haar functions have been used from 1910
when they were introduced by the Hungarian
mathematician Alfred Haar[9]. Haar wavelet is
discontinuous, and resembles a step function. It
represents the same wavelets Daubechiesdb1. In
mathematics, the Haar wavelet is a certain
sequence of functions. Haar used these functions
to give an example of a countable orthonormal
system for the space of square-
integrable functions on the real line. The study of
wavelets, and even the term "wavelet", did not
come until much later. The technical
disadvantage lies in the discontinuity of Haar
wavelet, and therefore it is not differentiable.
This property can, however, be an advantage for
the analysis of signals with sudden transitions,
such as monitoring of tool failure in machines.
d) Gabor Filter
In image processing, a Gabor filter, named after
Dennis Gabor, is a linear filter used for edge
detection[10]. Frequency and orientation
representations of Gabor filters are similar to
those of the human visual system, and they have
been found to be particularly appropriate for
texture representation and discrimination. In the
spatial domain, a 2D Gabor filter is a Gaussian
kernel function modulated by a sinusoidal plane
wave. The Gabor filters are self-similar: all filters
can be generated from one mother wavelet by
dilation and rotation.J. G. Daugman discovered
that simple cells in the visual cortex of
mammalian brains can be modeled by Gabor
functions. Thus, image analysis by the Gabor
functions is similar to perception in the human
visual system.
e) Daubechies(db) wavelet
Daubechies constructed the first wavelet
family of scale functions that are orthogonal and
have finite vanishing moments, i.e., compact
support [9]. This property insures that the number
of non-zero coefficients in the associated filter is
finite. This is very useful for local analysis. The
Haar wavelet is the basis of the simplest wavelet
transform. It is also the only symmetric wavelet
in the Daubechies family and the only one that
has an explicit expression in discrete form. Haar
wavelets are related to a mathematical operation
called Haar transform, which serves as a
prototype for all other wavelet transforms.
For the Daubechies wavelet transforms, the
scaling signals and wavelets have slightly longer
supports, i.e., they produce averages and
differences using just a few more values from the
signal. This slight change, however, provides a
tremendous improvement in the capabilities of
these new transforms. They provide us with a set
of powerful tools for performing basic signal
processing tasks. This family of wavelets with
one parameter, due to Daubechies is the first one
to make it possible to handle orthogonal wavelets
with compact support and arbitrary regularity.
4. RESULTS AND DISCUSSION
This section, deals with the investigation
consequences of combining different biometric
feature extraction algorithm. Specifically at
feature level fusion, Min-Max normalization rule
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to measure the performance of multi-algorithms
system. In all the experiments, performance is
measured in terms of Recognition rate, Recall,
Precision and F-measure. First the performance
of a single modality biometric system is
measured; later the results for multi-algorithmic
biometric system are evaluated.
CASIA Iris Image Database Version 1.0
(CASIA-IrisV1) is used for experimentations, it
includes 756 iris images from 108 eyes[14]. For
each eye, 7 images are captured in two sessions
with our self-developed device CASIA close-up
iris camera, where three samples are collected in
the first session and four in the second session.
According to our experimental study, In table:1,
it is found that as individual algorithm LPQ,
Gabor Filter, Haar, Db8 and LBP independently
results in 89%, 68%, 66.5%, 73% and 61%
accuracy respectively. Performance of LPQ is the
superior compare to other feature extraction
methods.
By analyzing the results in Table-2, it can be
observed that; The fusion of two feature
extraction algorithms at feature level gives higher
accuracy than single feature extraction method.
We can also infer that, combination of LPB and
LPQ algorithms outperforms the other existing
combinations set.
However, Db8 and Haar algorithms combination
is the least performance even compare to a single
algorithm of LPQ. From Table -3, we can
observe that there is no such impact in
performance. Compare to its previous two
algorithm fusion, however one can find the
reduction in accuracy by introducing third feature
extraction algorithm. Hence, choosing best
combination plays a major role than increase the
feature extraction algorithms.
Table-1: Performance of Single feature extraction
algorithm
Table-2: Performance of two feature extraction
algorithm
Table-3: Performance of three feature extraction
algorithm
5. CONCLUSION
Feature
extraction
LPQ Gabor Haar Db8 LBP
Recognition
rate
89 68 66.5 73 61
Recall 89 68 66.5 73 61
Precision 90.66 66.91 68.32 75.08 63.23
F-measure 89.82 67.45 67.39 74.02 62.09
Algorithm
1
Algorithm
2
Recognition Recall Precision
F-
measure
Db8 Haar 85.5 85.5 87.7 86.6
Db8 LPQ 92.0 92.0 90.6 91.3
Db8 LBP 91.5 91.5 91.1 91.3
Db8 Gabor 84.5 84.5 84.8 84.6
Haar LPQ 92.0 92.0 90.5 91.2
Haar Gabor 85.0 85.0 84.7 84.8
Haar LBP 90.5 90.5 90.2 90.3
LPQ LBP 95.0 95.0 93.8 94.4
LPQ Gabor 89.0 89.0 89.1 89.0
Gabor LBP 88.0 88.0 86.5 87.2
Algorithm
1
Algorithm
2
Algorithm
3
Recognition Recall Precision
F-
measure
LBP LPQ Db8 93.5 93.5 92 92.8
Db8 Haar LPQ 90.5 90.5 89.8 90.14
Db8 Haar LBP 90 90 90.4 90.2
Haar Gabor LPQ 90.5 90.5 89.8 90.1
Haar Gabor LBP 88.5 88.5 88.2 88.3
LPQ Gabor LBP 94.5 94.5 93.7 94.1
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From the analysis of experimental results and
observations, it can be concluded that; The
performance of fusion of three feature extraction
algorithms, at feature level on feature
normalization of Min-Max rule. Does not have
expected performance improvement over the two
feature extraction algorithms. Fusion of three
algorithms in iris recognition, the performance is
same or decreased when compared to the
performance of fusion of two algorithms. One
such case in our experiment is fusion of LBP and
LPQ has 95% accuracy, when we introduce one
more feature extraction algorithm to this
combination, the performance is decreased
drastically. The only exception is when fusing
three algorithms of combination Db8 Haar and
LPQ, which gained some good performance
when compared to fusion of two algorithms. The
performance of fusion of three algorithms, does
not have performance improvement over the
fusion of two which are the same performance in
the best case. This is due to fusion of multiple
redundant features at feature level, which also
causes performance degradation of biometric
system.
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