This document discusses two techniques for finger knuckle print recognition: Gabor filtering and Dual Tree Complex Wavelet Transform (DT-CWT). Gabor filtering is applied to extract spatial-frequency and orientation information from finger knuckle print images. DT-CWT is also used for feature extraction and is found to provide more discriminative features while being less computationally complex than Gabor filtering. The document analyzes the PolyU FKP database of 7920 images using both techniques and compares their performance based on metrics like false acceptance rate, true acceptance rate, and false rejection rate to evaluate the pros and cons of each approach.
Development and Implementation of VLSI Reconfigurable Architecture for Gabor ...Dr. Amarjeet Singh
The Gabor filter is a very effective tool in visual
search approaches and multimedia applications. This filter
provides high resolution in time-frequency domains and thus
finds use in object recognition, character recognition and
pattern recognition applications. Medical Image analysis
using image processing algorithms is one of the best ways of
diagnosing diseases inside human body. The Gabor wavelets
resemble the visual cortex cell operation of mammalian
brains and hence are best suited for biological image analysis.
A Tonsillitis detection system is proposed here using Gabor
filtering approach. This system detects the presence of
Tonsillitis from the tonsils images. A suitable VLSI
architecture for the implementation of the Gabor filter was
modeled in Verilog using Xilinx tool and simulated using the
tonsils test images. The proposed system was successful in
detecting the presence of Tonsillitis from the diseased tonsils
image. The complete system was then synthesized and
implemented on FPGA Artix 7. The design was capable of
operating at a maximum frequency of 394.563 MHz.
MultiModal Identification System in Monozygotic TwinsCSCJournals
With the increase in the number of twin births in recent decades, there is a need to develop alternate approaches that can secure the biometric system. In this paper an effective fusion scheme is presented that combines information presented by multiple domain experts based on the rank-level fusion integration method. The developed multimodal biometric system possesses a number of unique qualities, starting from utilizing Fisher’s Linear Discriminant methods for face matching, Principal Component Analysis for fingerprint matching and Local binary pattern features for iris matching and fused the information for effective recognition and authentication The importance of considering these boundary conditions, such as twins, where the possibility of errors is maximum will lead us to design a more reliable and robust security system.The proposed approach is tested on a real database consisting of 50 pair of identical twin images and shows promising results compared to other techniques. The Receiver Operating Characteristics also shows that the proposed method is superior compared to other techniques under study.
A Hybrid Approach to Face Detection And Feature Extractioniosrjce
IOSR Journal of Computer Engineering (IOSR-JCE) is a double blind peer reviewed International Journal that provides rapid publication (within a month) of articles in all areas of computer engineering and its applications. The journal welcomes publications of high quality papers on theoretical developments and practical applications in computer technology. Original research papers, state-of-the-art reviews, and high quality technical notes are invited for publications.
Handwritten Character Recognition: A Comprehensive Review on Geometrical Anal...iosrjce
IOSR Journal of Computer Engineering (IOSR-JCE) is a double blind peer reviewed International Journal that provides rapid publication (within a month) of articles in all areas of computer engineering and its applications. The journal welcomes publications of high quality papers on theoretical developments and practical applications in computer technology. Original research papers, state-of-the-art reviews, and high quality technical notes are invited for publications.
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.
Development and Implementation of VLSI Reconfigurable Architecture for Gabor ...Dr. Amarjeet Singh
The Gabor filter is a very effective tool in visual
search approaches and multimedia applications. This filter
provides high resolution in time-frequency domains and thus
finds use in object recognition, character recognition and
pattern recognition applications. Medical Image analysis
using image processing algorithms is one of the best ways of
diagnosing diseases inside human body. The Gabor wavelets
resemble the visual cortex cell operation of mammalian
brains and hence are best suited for biological image analysis.
A Tonsillitis detection system is proposed here using Gabor
filtering approach. This system detects the presence of
Tonsillitis from the tonsils images. A suitable VLSI
architecture for the implementation of the Gabor filter was
modeled in Verilog using Xilinx tool and simulated using the
tonsils test images. The proposed system was successful in
detecting the presence of Tonsillitis from the diseased tonsils
image. The complete system was then synthesized and
implemented on FPGA Artix 7. The design was capable of
operating at a maximum frequency of 394.563 MHz.
MultiModal Identification System in Monozygotic TwinsCSCJournals
With the increase in the number of twin births in recent decades, there is a need to develop alternate approaches that can secure the biometric system. In this paper an effective fusion scheme is presented that combines information presented by multiple domain experts based on the rank-level fusion integration method. The developed multimodal biometric system possesses a number of unique qualities, starting from utilizing Fisher’s Linear Discriminant methods for face matching, Principal Component Analysis for fingerprint matching and Local binary pattern features for iris matching and fused the information for effective recognition and authentication The importance of considering these boundary conditions, such as twins, where the possibility of errors is maximum will lead us to design a more reliable and robust security system.The proposed approach is tested on a real database consisting of 50 pair of identical twin images and shows promising results compared to other techniques. The Receiver Operating Characteristics also shows that the proposed method is superior compared to other techniques under study.
A Hybrid Approach to Face Detection And Feature Extractioniosrjce
IOSR Journal of Computer Engineering (IOSR-JCE) is a double blind peer reviewed International Journal that provides rapid publication (within a month) of articles in all areas of computer engineering and its applications. The journal welcomes publications of high quality papers on theoretical developments and practical applications in computer technology. Original research papers, state-of-the-art reviews, and high quality technical notes are invited for publications.
Handwritten Character Recognition: A Comprehensive Review on Geometrical Anal...iosrjce
IOSR Journal of Computer Engineering (IOSR-JCE) is a double blind peer reviewed International Journal that provides rapid publication (within a month) of articles in all areas of computer engineering and its applications. The journal welcomes publications of high quality papers on theoretical developments and practical applications in computer technology. Original research papers, state-of-the-art reviews, and high quality technical notes are invited for publications.
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.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
Authentication of Degraded Fingerprints Using Robust Enhancement and Matching...IDES Editor
Biometric system is an automated method of
identifying a person based on physiological, biology and
behavioural traits. The physiological traits in include face,
fingerprint, palm print and iris which remains permanent
throughout an individual life time. In the event that these
physiological traits have been degraded then the
authentication of an individual becomes very difficult. The
challenge of restoring a degraded physiological image to an
acceptable appearance in order to authenticate an individual
is very enormous. Fingerprint is one of the most extensively
used biometric systems for authentication in areas where
security is of high importance. This is due to their accuracy
and reliability. However, extracting features out of degraded
fingerprints is the most challenging in order to obtain high
fingerprint matching performance. This paper endeavors to
enhance the clarity of fingerprint minutiae, removing false
minutiae and improve the matching performance using a
robust Gabor Filtering Technique (GFT) and Back Propagation
Artificial Neural Network (BP-ANN). The experiments showed
a remarkable improvement in the performance of the system.
Image De-noising and Enhancement for Salt and Pepper Noise using Genetic Algo...IDES Editor
Image Enhancement through De-noising is one of
the most important applications of Digital Image Processing
and is still a challenging problem. Images are often received
in defective conditions due to usage of Poor image sensors,
poor data acquisition process and transmission errors etc.,
which creates problems for the subsequent process to
understand such images. The proposed Genetic filter is capable
of removing noise while preserving the fine details, as well as
structural image content. It can be divided into: (i) de-noising
filtering, and (ii) enhancement filtering. Image Denoising
and enhancement are essential part of any image processing
system, whether the processed information is utilized for visual
interpretation or for automatic analysis. The Experimental
results performed on a set of standard test images for a wide
range of noise corruption levels shows that the proposed filter
outperforms standard procedures for salt and pepper removal
both visually and in terms of performance measures such as
PSNR.Genetic algorithms will definitely helpful in solving
various complex image processing tasks in the future.
Efficient Small Template Iris Recognition System Using Wavelet TransformCSCJournals
Iris recognition is known as an inherently reliable biometric technique for human identification. Feature extraction is a crucial step in iris recognition, and the trend nowadays is to reduce the size of the extracted features. Special efforts have been applied in order to obtain low templates size and fast verification algorithms. These efforts are intended to enable a human authentication in small embedded systems, such as an Integrated Circuit smart card. In this paper, an effective eyelids removing method, based on masking the iris, has been applied. Moreover, an efficient iris recognition encoding algorithm has been employed. Different combination of wavelet coefficients which quantized with multiple quantization levels are used and the best wavelet coefficients and quantization levels are determined. The system is based on an empirical analysis of CASIA iris database images. Experimental results show that this algorithm is efficient and gives promising results of False Accept Ratio (FAR) = 0% and False Reject Ratio (FRR) = 1% with a template size of only 364 bits.
ABSTRACT Feature extraction plays a vital role in the analysis and interpretation of remotely sensed data. The two important components of Feature extraction are Image enhancement and information extraction. Image enhancement techniques help in improving the visibility of any portion or feature of the image. Information extraction techniques help in obtaining the statistical information about any particular feature or portion of the image. This presented work focuses on the various feature extraction techniques and area of optical character recognition is a particularly important in Image processing. Keywords— Image character recognition, Methods for Feature Extraction, Basic Gabor Filter, IDA, and PCA.
Microarray Data Classification Using Support Vector MachineCSCJournals
DNA microarrays allow biologist to measure the expression of thousands of genes simultaneously on a small chip. These microarrays generate huge amount of data and new methods are needed to analyse them. In this paper, a new classification method based on support vector machine is proposed. The proposed method is used to classify gene expression data recorded on DNA microarrays. It is found that the proposed method is faster than neural network and the classification performance is not less than neural network.
WAVELET PACKET BASED IRIS TEXTURE ANALYSIS FOR PERSON AUTHENTICATIONsipij
There is considerable rise in the research of iris recognition system over a period of time. Most of the
researchers has been focused on the development of new iris pre-processing and recognition algorithms for
good quail iris images. In this paper, iris recognition system using Haar wavelet packet is presented.
Wavelet Packet Transform (WPT ) which is extension of discrete wavelet transform has multi-resolution
approach. In this iris information is encoded based on energy of wavelet packets.. Our proposed work
significantly decreases the error rate in recognition of noisy images. A comparison of this work with nonorthogonal Gabor wavelets method is done. Computational complexity of our work is also less as
compared to Gabor wavelets method.
A Novel Method for Detection of Architectural Distortion in MammogramIDES Editor
Among various breast abnormalities architectural
distortion is the most difficult type of tumor to detect. When
area of interest is medical image data, the major concern is to
develop methodologies which are faster in computation and
relatively noise free in processing. This paper is an extension
of our own work where we propose a hybrid methodology that
combines a Gabor filtration with directional filters over the
directional spectrum for digitized mammogram processing.
The most commendable thing in comparison to other
approaches is that complexity has been lowered as well as the
computation time has also been reduced to a large extent. On
the MIAS database we achieved a sensitivity of 89 %.
Land Boundary Detection of an Island using improved Morphological OperationCSCJournals
Image analysis is one of the important tasks to obtain the information about earth surface. To detect and mark a particular land area, it is required to have the image from remote place. To recognize the same, the accurate boundary of that area has to be detected. In this paper, the example of remote sensing image has been considered. The accurate detection of the boundary is a complex task. A novel method has been proposed in this paper to detect the boundary of such land. Mathematical morphology is a simple and efficient method for this type of task. The morphological analysis is performed using structure elements (SE). By using mathematical morphology the images can be enhanced and then the boundary can be detected easily. Simultaneously the noise is removed by using the proposed model. The results exhibit the performance of the proposed method. Keywords: Remote Sensing images ; Edge detection; Gray- scale Morphological analysis, Structuring Element (SE).
Extraction of spots in dna microarrays using genetic algorithmsipij
DNA microarray technology is an eminent tool for genomic studies. Accurate extraction of spots is a
crucial issue since biological interpretations depend on it. The image analysis starts with the formation of
grid, which is a laborious process requiring human intervention. This paper presents a method for optimal
search of the spots using genetic algorithm without formation of grid. The information of every spot is
extracted by obtaining a pixel belonging to that spot. The method developed selects pixels of high intensity
in the image, thereby spot is recognized. The objective function, which is implemented, helps in identifying
the exact pixel. The algorithm is applied to different sizes of sub images and features of the spots are
obtained. It is found that there is a tradeoff between accuracy in the number of spots identified and time
required for processing the image. Segmentation process is independent of shape, size and location of the
spots. Background estimation is one step process as both foreground and complete spot are realized.
Coding of the proposed algorithm is developed in MATLAB-7 and applied to cDNA microarray images.
This approach provides reliable results for identification of even low intensity spots and elimination of
spurious spots.
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
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
Spot Edge Detection in cDNA Microarray Images using Window based Bi-Dimension...idescitation
Ongoing Microarray is an increasingly playing a crucial role applied in the field
of medical and biological operations. The initiator of Microarray technology is M. Schena et
al. [1] and from past few years microarrays have begun to be used in many fields such as
biomedicine, mostly on cancer and Diabetic, and medical diagnoses. A Deoxyribonucleic
Acid (DNA) microarray is a collection of microscopic DNA spots attached to a solid surface,
such as glass, plastic or silicon chip forming an array. Processing of DNA microarray image
analysis includes three tasks: gridding, segmentation and intensity extraction and at the
stage of processing, the irregularities of shape and spot position which leads to generate
significant errors. This article presents a new spot edge detection method using Window
based Bi-dimensional Empirical Mode Decomposition. On separating spots form the
background area and to decreases the probability of errors and gives more accurate
information about the states of spots we are proposing a spot edge detection via WBEMD.
By using this method we can identify the spots with low density, which leads to increasing
the performance of cDNA microarray images.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
Authentication of Degraded Fingerprints Using Robust Enhancement and Matching...IDES Editor
Biometric system is an automated method of
identifying a person based on physiological, biology and
behavioural traits. The physiological traits in include face,
fingerprint, palm print and iris which remains permanent
throughout an individual life time. In the event that these
physiological traits have been degraded then the
authentication of an individual becomes very difficult. The
challenge of restoring a degraded physiological image to an
acceptable appearance in order to authenticate an individual
is very enormous. Fingerprint is one of the most extensively
used biometric systems for authentication in areas where
security is of high importance. This is due to their accuracy
and reliability. However, extracting features out of degraded
fingerprints is the most challenging in order to obtain high
fingerprint matching performance. This paper endeavors to
enhance the clarity of fingerprint minutiae, removing false
minutiae and improve the matching performance using a
robust Gabor Filtering Technique (GFT) and Back Propagation
Artificial Neural Network (BP-ANN). The experiments showed
a remarkable improvement in the performance of the system.
Image De-noising and Enhancement for Salt and Pepper Noise using Genetic Algo...IDES Editor
Image Enhancement through De-noising is one of
the most important applications of Digital Image Processing
and is still a challenging problem. Images are often received
in defective conditions due to usage of Poor image sensors,
poor data acquisition process and transmission errors etc.,
which creates problems for the subsequent process to
understand such images. The proposed Genetic filter is capable
of removing noise while preserving the fine details, as well as
structural image content. It can be divided into: (i) de-noising
filtering, and (ii) enhancement filtering. Image Denoising
and enhancement are essential part of any image processing
system, whether the processed information is utilized for visual
interpretation or for automatic analysis. The Experimental
results performed on a set of standard test images for a wide
range of noise corruption levels shows that the proposed filter
outperforms standard procedures for salt and pepper removal
both visually and in terms of performance measures such as
PSNR.Genetic algorithms will definitely helpful in solving
various complex image processing tasks in the future.
Efficient Small Template Iris Recognition System Using Wavelet TransformCSCJournals
Iris recognition is known as an inherently reliable biometric technique for human identification. Feature extraction is a crucial step in iris recognition, and the trend nowadays is to reduce the size of the extracted features. Special efforts have been applied in order to obtain low templates size and fast verification algorithms. These efforts are intended to enable a human authentication in small embedded systems, such as an Integrated Circuit smart card. In this paper, an effective eyelids removing method, based on masking the iris, has been applied. Moreover, an efficient iris recognition encoding algorithm has been employed. Different combination of wavelet coefficients which quantized with multiple quantization levels are used and the best wavelet coefficients and quantization levels are determined. The system is based on an empirical analysis of CASIA iris database images. Experimental results show that this algorithm is efficient and gives promising results of False Accept Ratio (FAR) = 0% and False Reject Ratio (FRR) = 1% with a template size of only 364 bits.
ABSTRACT Feature extraction plays a vital role in the analysis and interpretation of remotely sensed data. The two important components of Feature extraction are Image enhancement and information extraction. Image enhancement techniques help in improving the visibility of any portion or feature of the image. Information extraction techniques help in obtaining the statistical information about any particular feature or portion of the image. This presented work focuses on the various feature extraction techniques and area of optical character recognition is a particularly important in Image processing. Keywords— Image character recognition, Methods for Feature Extraction, Basic Gabor Filter, IDA, and PCA.
Microarray Data Classification Using Support Vector MachineCSCJournals
DNA microarrays allow biologist to measure the expression of thousands of genes simultaneously on a small chip. These microarrays generate huge amount of data and new methods are needed to analyse them. In this paper, a new classification method based on support vector machine is proposed. The proposed method is used to classify gene expression data recorded on DNA microarrays. It is found that the proposed method is faster than neural network and the classification performance is not less than neural network.
WAVELET PACKET BASED IRIS TEXTURE ANALYSIS FOR PERSON AUTHENTICATIONsipij
There is considerable rise in the research of iris recognition system over a period of time. Most of the
researchers has been focused on the development of new iris pre-processing and recognition algorithms for
good quail iris images. In this paper, iris recognition system using Haar wavelet packet is presented.
Wavelet Packet Transform (WPT ) which is extension of discrete wavelet transform has multi-resolution
approach. In this iris information is encoded based on energy of wavelet packets.. Our proposed work
significantly decreases the error rate in recognition of noisy images. A comparison of this work with nonorthogonal Gabor wavelets method is done. Computational complexity of our work is also less as
compared to Gabor wavelets method.
A Novel Method for Detection of Architectural Distortion in MammogramIDES Editor
Among various breast abnormalities architectural
distortion is the most difficult type of tumor to detect. When
area of interest is medical image data, the major concern is to
develop methodologies which are faster in computation and
relatively noise free in processing. This paper is an extension
of our own work where we propose a hybrid methodology that
combines a Gabor filtration with directional filters over the
directional spectrum for digitized mammogram processing.
The most commendable thing in comparison to other
approaches is that complexity has been lowered as well as the
computation time has also been reduced to a large extent. On
the MIAS database we achieved a sensitivity of 89 %.
Land Boundary Detection of an Island using improved Morphological OperationCSCJournals
Image analysis is one of the important tasks to obtain the information about earth surface. To detect and mark a particular land area, it is required to have the image from remote place. To recognize the same, the accurate boundary of that area has to be detected. In this paper, the example of remote sensing image has been considered. The accurate detection of the boundary is a complex task. A novel method has been proposed in this paper to detect the boundary of such land. Mathematical morphology is a simple and efficient method for this type of task. The morphological analysis is performed using structure elements (SE). By using mathematical morphology the images can be enhanced and then the boundary can be detected easily. Simultaneously the noise is removed by using the proposed model. The results exhibit the performance of the proposed method. Keywords: Remote Sensing images ; Edge detection; Gray- scale Morphological analysis, Structuring Element (SE).
Extraction of spots in dna microarrays using genetic algorithmsipij
DNA microarray technology is an eminent tool for genomic studies. Accurate extraction of spots is a
crucial issue since biological interpretations depend on it. The image analysis starts with the formation of
grid, which is a laborious process requiring human intervention. This paper presents a method for optimal
search of the spots using genetic algorithm without formation of grid. The information of every spot is
extracted by obtaining a pixel belonging to that spot. The method developed selects pixels of high intensity
in the image, thereby spot is recognized. The objective function, which is implemented, helps in identifying
the exact pixel. The algorithm is applied to different sizes of sub images and features of the spots are
obtained. It is found that there is a tradeoff between accuracy in the number of spots identified and time
required for processing the image. Segmentation process is independent of shape, size and location of the
spots. Background estimation is one step process as both foreground and complete spot are realized.
Coding of the proposed algorithm is developed in MATLAB-7 and applied to cDNA microarray images.
This approach provides reliable results for identification of even low intensity spots and elimination of
spurious spots.
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
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
Spot Edge Detection in cDNA Microarray Images using Window based Bi-Dimension...idescitation
Ongoing Microarray is an increasingly playing a crucial role applied in the field
of medical and biological operations. The initiator of Microarray technology is M. Schena et
al. [1] and from past few years microarrays have begun to be used in many fields such as
biomedicine, mostly on cancer and Diabetic, and medical diagnoses. A Deoxyribonucleic
Acid (DNA) microarray is a collection of microscopic DNA spots attached to a solid surface,
such as glass, plastic or silicon chip forming an array. Processing of DNA microarray image
analysis includes three tasks: gridding, segmentation and intensity extraction and at the
stage of processing, the irregularities of shape and spot position which leads to generate
significant errors. This article presents a new spot edge detection method using Window
based Bi-dimensional Empirical Mode Decomposition. On separating spots form the
background area and to decreases the probability of errors and gives more accurate
information about the states of spots we are proposing a spot edge detection via WBEMD.
By using this method we can identify the spots with low density, which leads to increasing
the performance of cDNA microarray images.
DCT AND DFT BASED BIOMETRIC RECOGNITION AND MULTIMODAL BIOMETRIC SECURITYIAEME Publication
This Research paper discusses the study and analysis conducted during this research on various techniques in biometric domain. A close glance on biometric enhancement techniques and their limitations are presented in this research paper. This process would enable researcher to understand the research contributions in the area of DCT and DFT based recognition and security, locate some crucial limitations of these notable research. This paper having summary about the different research papers that applicable to our topic of research which mentioned above. Biometric Recognition and security is a most important subject of research in this area of image processing.
A Spectral Domain Dominant Feature Extraction Algorithm for Palm-print Recogn...CSCJournals
In this paper, a spectral feature extraction algorithm is proposed for palm-print recognition, which can efficiently capture the detail spatial variations in a palm-print image. The entire image is segmented into several spatial modules and the task of feature extraction is carried out using two dimensional Fourier transform within those spatial modules. A dominant spectral feature selection algorithm is proposed, which offers an advantage of very low feature dimension and results in a very high within-class compactness and between-class separability of the extracted features. A principal component analysis is performed to further reduce the feature dimension. From our extensive experimentations on different palm-print databases, it is found that the performance of the proposed method in terms of recognition accuracy and computational complexity is superior to that of some of the recent methods.
Symbolic representation and recognition of gait an approach based on lbp of ...sipij
Gait is one of the biometric techniques used to identify an individual from a distance by his/her walking
style. Gait can be recognized by studying the static and dynamic part variations of individual body contour
during walk. In this paper, an interval value based representation and recognition of gait using local
binary pattern (LBP) of split gait energy images is proposed. The gait energy image (GEI) of a subject is
split into four equal regions. LBP technique is applied to each region to extract features and the extracted
features are well organized. The proposed representation technique is capable of capturing variations in
gait due to change in cloth, carrying a bag and different instances of normal walking conditions more
effectively. Experiments are conducted on the standard and considerably large database (CASIA database
B) and newly created University of Mysore (UOM) gait dataset to study the efficacy of the proposed gait
recognition system. The proposed system being robust to handle variations has shown significant
improvement in recognition rate.
Iris recognition become one of the most accurate and reliable steadfast human biometric recognition system of the decad. This paper presents an accurate framework for iris recognition system using hybrid algorithm in preprocess and feature extraction section. The proposed model for iris recognition with significant feature extraction was divided into three main levels. First level is having pre-processing steps which are necessary for the desired tasks. Our model deploys on three types of datasets such as UBIRIS, CASIA, and MMU and gets optimal results for performing activity. At last, perform matching process with decision based classifier for iris recognition with acceptance or rejection rates. Experimental based results provide for analysis according to the false receipt rate and false refusal amount. In the third level, the error rate will be checked along with some statistical measures for final optimal results. Constructed on the outcome the planned method provided the most efficient effect as compared to the rest of the approach.
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.
Multi-feature Fusion Using SIFT and LEBP for Finger Vein RecognitionTELKOMNIKA JOURNAL
In this paper, multi-feature fusion using Scale Invariant Feature Transform (SIFT) and Local
Extensive Binary Pattern (LEBP) was proposed to obtain a feature that could resist degradation problems
such as scaling, rotation, translation and varying illumination conditions. SIFT feature had a capability to
withstand degradation due to changes in the condition of the image scale, rotation and translation.
Meanwhile, LEBP feature had resistance to gray level variations with richer and discriminatory local
characteristics information. Therefore the fusion technique is used to collect important information from
SIFT and LEBP feature.The resulting feature of multi-feature fusion using SIFT and LEBP feature would be
processed by Learning Vector Quantization (LVQ) method to determine whether the testing image could
be recognized or not. The accuracy value could achieve 97.50%, TPR at 0.9400 and FPR at 0.0128 in
optimum condition. That was a better result than only use SIFT or LEBP feature.
A SURVEY ON VARIOUS APPROACHES TO FINGERPRINT MATCHING FOR PERSONAL VERIFICAT...IJCSES Journal
Automatic Fingerprint authentication for personal identification and verification has received considerable
attention over the past decades among various biometric techniques because of the distinctiveness and
persistence properties of fingerprints. Now fingerprints are set to explode in popularity as they are being
used to secure smart phones and to authorize payments in online stores. The main objective of this paper is
to review the extensive research work that has been done over the past decade and discuss the various
approaches proposed for fingerprint matching. The proposed methods were based on 2D correlation in the
spatial and frequency domains, Artificial Neural Networks, Hough transform, Fourier transform, graphs,
local texture, ridge geometry etc. All these different techniques have their pros and cons. This paper also
provides the performance comparison of several existing methods proposed by researchers in fing
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.
IRDO: Iris Recognition by fusion of DTCWT and OLBPIJERA Editor
Iris Biometric is a physiological trait of human beings. In this paper, we propose Iris an Recognition using
Fusion of Dual Tree Complex Wavelet Transform (DTCWT) and Over Lapping Local Binary Pattern (OLBP)
Features. An eye is preprocessed to extract the iris part and obtain the Region of Interest (ROI) area from an iris.
The complex wavelet features are extracted for region from the Iris DTCWT. OLBP is further applied on ROI to
generate features of magnitude coefficients. The resultant features are generated by fusing DTCWT and OLBP
using arithmetic addition. The Euclidean Distance (ED) is used to compare test iris with database iris features to
identify a person. It is observed that the values of Total Success Rate (TSR) and Equal Error Rate (EER) are
better in the case of proposed IRDO compared to the state-of-the art techniques.
COMPARATIVE ANALYSIS OF MINUTIAE BASED FINGERPRINT MATCHING ALGORITHMSijcsit
Biometric matching involves finding similarity between fingerprint images.The accuracy and speed of the
matching algorithmdetermines its effectives. This researchaims at comparing two types of matching
algorithms namely(a) matching using global orientation features and (b) matching using minutia triangulation.The comparison is done using accuracy, time and number of similar features. The experiment is conducted on a datasets of 100 candidates using four (4) fingerprints from each candidate. The data is sampled from a mass registration conducted by a reputable organization in Kenya.Theresearch reveals that fingerprint matching based on algorithm (b) performs better in speed with an average of 38.32 milliseconds
as compared to matching based on algorithm (a) with an average of 563.76 milliseconds. On accuracy,algorithm(a) performs better with an average accuracy of 0.142433 as compared to algorithm (b) with an average accuracy score of 0.004202.
Highly Secured Bio-Metric Authentication Model with Palm Print IdentificationIJERA Editor
For securing personal identifications and highly secure identification problems, biometric technologies will
provide higher security with improved accuracy. This has become an emerging technology in recent years due to
the transaction frauds, security breaches and personal identification etc. The beauty of biometric technology is it
provides a unique code for each person and it can’t be copied or forged by others. To overcome the draw backs
of finger print identification systems, here in this paper we proposed a palm print based personal identification
system, which is a most promising and emerging research area in biometric identification systems due to its
uniqueness, scalability, faster execution speed and large area for extracting the features. It provides higher
security over finger print biometric systems with its rich features like wrinkles, continuous ridges, principal
lines, minutiae points, and singular points. The main aim of proposed palm print identification system is to
implement a system with higher accuracy and increased speed in identifying the palm prints of several users.
Here, in this we presented a highly secured palm print identification system with extraction of region of interest
(ROI) with morphological operation there by applying un-decimated bi-orthogonal wavelet (UDBW) transform
to extract the low level features of registered palm prints to calculate its feature vectors (FV) then after the
comparison is done by measuring the distance between registered palm feature vector and testing palm print
feature vector. Simulation results show that the proposed biometric identification system provides more
accuracy and reliable recognition rate
Iris recognition based on 2D Gabor filterIJECEIAES
Iris recognition is a type of biometrics technology that is based on physiological features of the human body. The objective of this research is to recognize and identify iris among many irises that are stored in a visual database. This study employed a left and right iris biometric framework for inclusion decision processing by combining image processing and artificial bee colony. The proposed approach was evaluated on a visual database of 280 colored iris pictures. The database was then divided into 28 clusters. Images were preprocessed and texture features were extracted based Gabor filters to capture both local and global details within an iris. The technique begins by comparing the attributes of the online-obtained iris picture with those of the visual database. This technique either generates a reject or approve message. The consequences of the intended work reflect the output’s accuracy and integrity. This is due to the careful selection of attributes, besides the deployment of an artificial bee colony and data clustering, which decreased complexity and eventually increased identification rate to 100%. We demonstrate that the proposed method achieves state-of-the-art performance and that our recommended procedures outperform existing iris recognition systems.
IMAGE SUBSET SELECTION USING GABOR FILTERS AND NEURAL NETWORKSijma
An automatic method for the selection of subsets of images, both modern and historic, out of a set of
landmark large images collected from the Internet is presented in this paper. This selection depends on the
extraction of dominant features using Gabor filtering. Features are selected carefully from a preliminary
image set and fed into a neural network as a training data. The method collects a large set of raw landmark
images containing modern and historic landmark images and non-landmark images. The method then
processes these images to classify them as landmark and non-landmark images. The classification
performance highly depends on the number of candidate features of the landmark.
I MAGE S UBSET S ELECTION U SING G ABOR F ILTERS A ND N EURAL N ETWORKSijma
An automatic method for the selection of subsets of
images, both modern and historic, out of a set of
landmark large images collected from the Internet i
s presented in this paper. This selection depends o
n the
extraction of dominant features using Gabor filteri
ng. Features are selected carefully from a prelimin
ary
image set and fed into a neural network as a traini
ng data. The method collects a large set of raw lan
dmark
images containing modern and historic landmark imag
es and non-landmark images. The method then
processes these images to classify them as landmark
and non-landmark images. The classification
performance highly depends on the number of candida
te features of the landmark.
Multibiometric systems are expected to be more reliable than unimodal biometric systems for personal identification due to the presence of multiple, fairly independent pieces of evidence e.g. Unique Identification Project "Aadhaar" of Government of India. In this paper, we present a novel wavelet based technique to perform fusion at the feature level and score level by considering two biometric modalities, face and fingerprint. The results indicate that the proposed technique can lead to substantial improvement in multimodal matching performance. The proposed technique is simple because of no preprocessing of raw biometric traits as well as no feature and score normalization.
DevOps and Testing slides at DASA ConnectKari Kakkonen
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UiPath Test Automation using UiPath Test Suite series, part 4DianaGray10
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Participants will gain insights into the responsibilities, challenges, and best practices associated with test management in SAP projects. Additionally, the webinar delves into the significance of heatmaps as a visual aid for identifying testing priorities, areas of risk, and resource allocation within SAP landscapes. Through this session, attendees can expect to enhance their understanding of test management principles while learning practical approaches to optimize testing processes in SAP environments using heatmap visualization techniques
What will you get from this session?
1. Insights into SAP testing best practices
2. Heatmap utilization for testing
3. Optimization of testing processes
4. Demo
Topics covered:
Execution from the test manager
Orchestrator execution result
Defect reporting
SAP heatmap example with demo
Speaker:
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
Essentials of Automations: Optimizing FME Workflows with ParametersSafe Software
Are you looking to streamline your workflows and boost your projects’ efficiency? Do you find yourself searching for ways to add flexibility and control over your FME workflows? If so, you’re in the right place.
Join us for an insightful dive into the world of FME parameters, a critical element in optimizing workflow efficiency. This webinar marks the beginning of our three-part “Essentials of Automation” series. This first webinar is designed to equip you with the knowledge and skills to utilize parameters effectively: enhancing the flexibility, maintainability, and user control of your FME projects.
Here’s what you’ll gain:
- Essentials of FME Parameters: Understand the pivotal role of parameters, including Reader/Writer, Transformer, User, and FME Flow categories. Discover how they are the key to unlocking automation and optimization within your workflows.
- Practical Applications in FME Form: Delve into key user parameter types including choice, connections, and file URLs. Allow users to control how a workflow runs, making your workflows more reusable. Learn to import values and deliver the best user experience for your workflows while enhancing accuracy.
- Optimization Strategies in FME Flow: Explore the creation and strategic deployment of parameters in FME Flow, including the use of deployment and geometry parameters, to maximize workflow efficiency.
- Pro Tips for Success: Gain insights on parameterizing connections and leveraging new features like Conditional Visibility for clarity and simplicity.
We’ll wrap up with a glimpse into future webinars, followed by a Q&A session to address your specific questions surrounding this topic.
Don’t miss this opportunity to elevate your FME expertise and drive your projects to new heights of efficiency.
Let's dive deeper into the world of ODC! Ricardo Alves (OutSystems) will join us to tell all about the new Data Fabric. After that, Sezen de Bruijn (OutSystems) will get into the details on how to best design a sturdy architecture within ODC.
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Watch this recorded webinar about real-time monitoring of application performance. See how to integrate Apache JMeter, the open-source leader in performance testing, with InfluxDB, the open-source time-series database, and Grafana, the open-source analytics and visualization application.
In this webinar, we will review the benefits of leveraging InfluxDB and Grafana when executing load tests and demonstrate how these tools are used to visualize performance metrics.
Length: 30 minutes
Session Overview
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During this webinar, we will cover the following topics while demonstrating the integrations of JMeter, InfluxDB and Grafana:
- What out-of-the-box solutions are available for real-time monitoring JMeter tests?
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Pradeep Chinnala, Senior Consultant Automation Developer @WonderBotz and UiPath MVP
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
Dev Dives: Train smarter, not harder – active learning and UiPath LLMs for do...UiPathCommunity
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See how to accelerate model training and optimize model performance with active learning
Learn about the latest enhancements to out-of-the-box document processing – with little to no training required
Get an exclusive demo of the new family of UiPath LLMs – GenAI models specialized for processing different types of documents and messages
This is a hands-on session specifically designed for automation developers and AI enthusiasts seeking to enhance their knowledge in leveraging the latest intelligent document processing capabilities offered by UiPath.
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Leading Change strategies and insights for effective change management pdf 1.pdf
A05610109
1. IOSR Journal of Engineering (IOSRJEN) www.iosrjen.org
ISSN (e): 2250-3021, ISSN (p): 2278-8719
Vol. 05, Issue 06 (June. 2015), ||V1|| PP 01-09
International organization of Scientific Research 1 | P a g e
Finger Knuckle Analysis: Gabor Vs DTCWT
Hanna Paulose, Er. Harbinder Singh
M.Tech Student Department of ECE SUS College of Engineering and Technology Tangori, Mohali, India
Assistant Professor Department of ECE SUS College of Engineering and Technology Tangori, Mohali, Punjab
Abstract: - Knuckle biometrics is one of the current trends in biometric human identification which offers a
reliable solution for verification. This paper analysis FKP recognition based on the behaviour of two different
filtering and classification methods. Firstly,Gabor Filter Banks techniques are applied for finger knuckle print
recognition and then the same database is analysed against Dual Tree Complex Wavelet Transform technique.
The experiment is evaluated to identify finger knuckle images using PolyU FKP database of 7920 images.
Finally, these two different systems are comparedfor false acceptance rate FAR,true acceptance, false rejection
rate FRR and true rejection. Extensive experiments are performed to evaluate both the techniques, and
experimental results show the pros and cons of using both the techniques for specific applications.
Keywords: - Finger Knuckle Print (FKP); Gabor Filter; Dual Tree Complex Wavelet Transform;
I. INTRODUCTION
Use of biometrics dates back over a thousand years, which is defined as the measure of human body
characteristics such as fingerprint, voice pattern, Iris and Hand measurement, Gait, Palm Print. It is a potent and
unique tool based on the physiological (anatomic) and behavioralcharacteristics of the human beingsas shown in
Fig.1.
Figure 1: Types of Biometric System
Typically, we can identify the following attributes of a biometric system such as
Uniqueness:It means that an identical feature should not appear in two different people.
Universality:This is the feature which ispresent/occurs in as many people as possible ie universally.
Permanence: This feature does not change over time,or we can say that it contrast very slowly.
Measurability: The possibility to measure the feature with relatively simple technical instruments
Acceptability:Its is the feature of the measurement in daily lives by all.
Circumvention:It is the toughness of the system to be deceived by fraudulent methods.
This paper discusses about the biometric identifier finger knuckle print (FKP), which is the outeror
exteriorsurface of the fingers of a person ie the phalangeal joint. Thisconfiguration or pattern of the exterior of
knuckle phalangeal joint is unique and dissimilar and can be used for authentication very efficiently and
effectively. Pattern of the finger knuckle is highly discriminative and makes the surface a unique biometric
identifier. The Finger Knuckle print recognition system typically contains data acquisition, ROI extraction,
feature extraction, coding and matching process. For the comparison universally accessiblePolyU FKP database
of 7920 images were utilized to study the features using different techniques and algorithms. The features of FKP
2. Finger Knuckle Analysis: Gabor Vs DTCWT
International organization of Scientific Research 2 | P a g e
are initiallyextracted using the Gabor Filter Banks and then the same database images are independently filtered
using Dual Tree Complex Wavelet Transform (DT-CWT).
II. RELATED STUDIES
The local characteristics or information of FKP was accessed using Scale Invariant Feature Transform
SIFT and Speed up Robust Features SURF technique. The SIFT Scale Invariant Feature Transform algorithm is
used to get the important ie key points using the scaling and invariant features which were matched to prove the
user authentication [1]. Ajay et.al, studied and suggested method of triangulation for authentication using hand
vein images of all finger’s finger knuckle s[2].Tao Kong et al.[3]proposed a extraction and classification method
based on hierarchical model for finger knuckle print recognition, rooted froman establishedstylefusion method of
scores obtained from the images. In the method which is under analysis, firstly Gabor feature has been taken as
the basic feature for finger knuckle print recognition and then a new decision rule is defined based on the
predefined threshold.G S Badrinath et al.[1] proposed a system which uses feature extraction with the help of
features that are local of improved FKP that are sifted out using the scale invariant feature transform and the
speeded up robust features extraction techniques. Nearest neighbour ratio technique is used for matching of
features of finger knuckle print and then matching scores of SIFT and SURF are fused using the weighted sum
rule.Lin et al. [4] using the outcomes of psycho-physics and neuro-physiology studies that show that image
perception is based on both local and global features, suggested, the Local Global Information Combination ie
(LGIC) technique. For local feature extraction and classification, the orientation information from the message is
extractedusingfour scales and six orientations Gabor filters and is encoded using the modest coding technique.
This process is appropriate for images containing ample line like constructions and has the benefits like
greataccurateness, sturdiness tobrightnessdisparities, and easy andfast matching. Subsequently the scale of the
Gabor filter is amplified to infinity by which the Fourier transform of the finger knuckle print image is obtained.
The Fourier constants of the image are taken as the global feature. For matching two good,competitivecode maps,
normalized Hamming distance obtained from used angular distance is used. BLPOC ieBand Limited Phase Only
Correlation is used to measure the correspondence between Fourier transforms ie Global Information of the
images. Thus both features ie the local and global features are extracted and the matched separately and two
distances obtained, d1 and d2 are then fused according to the rule distance given in Matcher Weighting (MW)
algorithm.
III. FKP RECOGNITION SYSTEM ARCHITECTURE
Figure 2: Schematic Diagram for FKP recognition
The system consists of FKP image acquisitionassembly followed by data processor whichconsists of
Region of Interest extraction, featureextraction and coding and finally matching isperformed to differentiate data
into imposter orgenuine. The study comprises of comparing two different filtering techniques.
Figure 3: (a,b) finger knuckle print images. (c,d) Region of Interest images.
3. Finger Knuckle Analysis: Gabor Vs DTCWT
International organization of Scientific Research 3 | P a g e
IV. FEATURE EXTRACTION AND MATCHING
This study features study of two different extraction technique and comparison between both of them.
The technique of the dual tree complex wavelet transform is initiated by the reason that it provisionsin removing
the effects of non-uniform brilliance, and the directional features provided by the dissimilar sub bands makes it
possible to identify edge information with different directionalities in the equivalent image. The consequential
complex-waveletbased feature information are more discriminating and distinguishing compared to the Gabor
wavelet-resultant features and at the same time are of lower dimension and time consuming when compared with
that of Gabor wavelets. 2-D dual-tree complex wavelet transform is more effective, less time complex and
computationallycompetent. Furthermore, in addition to the reliable and capable classification performances,
method 2-D dual-tree complex wavelet transform has a really low computational complexity.
Methodology
The study uses 2D Gabor filters and 2D Dual Tree Complex Wavelet Transform (DT-CWT) to extract
the image local orientation information. This information is then employed to extract and represent the finger
knuckle print recognition features. While matching of two knuckles, the Euclidian distance or hamming distance
is used to measure the similarity.
Feature Extraction
Feature extraction is very important step in pattern recognition because of poor quality and its necessary
to capture all options in finger knuckle image for associate economic and competitive and reasonable matching.
The effective approachesfor matching two coarsetexturedlike biometric pictures is to decide their identical or
similarity in spectral domain depiction of mistreatment the section information. Firstly, intra-class
differencesshould be small i.e. features derived from different samples of the same class should be close enough.
Secondly, the inter-class separation or differences should be large which means that features derived from
samples of different classes must differ significantly to ensure there is no matching between two different
knuckles. Also information or feature should be independent of the size, rotation and location of the pattern. 2D
Dual tree complex waveletis independent with regards to translation, rotation and scale, and therefore can be used
for pre-processing or extracting featuresof images.
Gabor Filtering Feature Extraction
The Gabor filtering technique can extract the spatial-frequency and orientation information from the
original signal [5]. It has been extensively used as a convolution filter for feature extraction to fulfill the feature
extraction job. For years together Gabor Filter technique has been broadly used as an effective toolfor feature and
information extraction job in face recognition, iris verification, fingerprintanalysis and palm print recognition
systems. In [6], Loris and Alessandra described a Gabor feature selection technique which can produce features
that are wavelength, phase, magnitude, orientation and bandwidth, which can be used separately or jointly in
different combinations in different systems. Kong calculated the three basic three features of Gabor Filter Banks
(magnitude, phase, and orientation) produced by the Gabor filter for face recognition system and concludes that
the orientation feature is the most robust, discriminative and distinctive feature [7]. T.S. Lee [8] evaluated the
situations under which a set of continuous 2D Gabor wavelets will provide a complete illustration of any image,
and also determinesimilar to the self image basedwavelet features and parameterizations which allow constant
reconstruction of the image from the filtered and superimposed images by summation even though the wavelets
formed in an orthonormal basis. In this paper, the 8 filters banks of Gabor filter is proposed by combining the
orientation, wavelength, phase and magnitude features using Gabor filter for knuckle print recognition.
Experiment and analysisresultscompare and verify the scheme against Dual Tree Complex Wavelet Transform
(DT-CWT) based on performance in FKP recognition. The Gabor filter banks has different methods in the
literature and here we adopt the one of the form proposed by Lee [8] as given below:
g 𝑥, 𝑦; 𝑓, 𝜃 = 𝑒
−
1
2
𝑥 𝜃
2
𝜎 𝑥
+
𝑦 𝜃
2
𝜎 𝑦
.cos (2𝜋𝑓 𝑥 𝜃 )
Where
𝑥 𝜃 = 𝑥 sin 𝜃 + 𝑦 cos 𝜃
𝑦 𝜃 = 𝑥 cos 𝜃 − 𝑦 sin 𝜃
and, g 𝑥, 𝑦; 𝑓, 𝜃 denotes the Gabor filter value in spatial domain x & y denote the x and y coordinates of the
Gabor filters, f denotes the frequency of the sinusoidal plane wave in the direction Ө from x-axis.𝜎𝑥 and 𝜎𝑦 denote
the standard deviations of the Gaussian envelope along x & y-axesseparately. Four parameters (θ, f,𝜎𝑥 , 𝜎𝑦)of
Gabor filtermust be specified for applying it to an image. The frequency of the filter is completely determined by
the local ridge frequency and the orientation is determined by the local ridge orientation. The selection of the
4. Finger Knuckle Analysis: Gabor Vs DTCWT
International organization of Scientific Research 4 | P a g e
values 𝜎𝑥 and 𝜎𝑦 involves trade off. The lager the values of 𝜎𝑥 and 𝜎𝑦 , the more stable and robust the filters are to
the discrepancies and noise in the fingerprint clip/ image, but also are more likely to generate spurious undesired
ridges and valleys.
On the other hand, the smaller the values of the filter, the less likely the filters are to introduce spurious
ridges and valleys but then they will be less effective in removing and clearing the noise. If𝜎𝑥 and 𝜎𝑦 are standard
deviations of the Gaussian envelope and the values are too large, the filter is more stable and robust to noise, but
is probable to smoothens the image to the extent that the ridges and valley details in the fingerprint are lost. If
𝜎𝑥 and 𝜎𝑦 readings are very small or less, the filter is not operative and effective in removing the noise. Gabor
technique is one of the common choice for texture and pattern analysis. There are different kinds of popular sets
of Gabor filters. These sets are generally designed based on illustration considerations. The 2D filter represented
by extracts the orientation and magnitude information at each pixel in digital knuckle image.At given threshold,
the probability of accepting imposter as correct person known as false acceptance rate FAR and likelihood of
rejecting genuine user as imposter is known as false rejection rate FRR are calculated. Equal Error Rate EER is an
ideal rate or optimal rate where FAR is equal to false rejection rate i.e FRR. Diagrammatically, Equal Error Rate,
EER is known or characterized as the crossing point or meeting point between false acceptance rate FAR and
false rejection rate FRR. It is commonly used to determine the overall accurateness of the system and serve as
comparative measure against the other biometric systems.
Dualtree Complex Wavelet Transform
Complex wavelet filters in two dimensions offer twodirectionalselectivity. So they are able to segregate
and differentiate all part of the two dimensional frequency space being implemented separately as two distinct
systems. Complex coefficient at each level aligned at angles of ±15º,±45º,±75º are generated from six bandpass
images. These features and characteristics are useful for pattern recognition of finger knuckle print. In this study
we present a new finger knuckle feature extraction method by using 2D DTCWT. The feature extraction scheme
is to use the multi-level coefficient of decomposition part of normalized finger image via 2D DT-CWT, which is
implemented using dual tree complex wavelet structure. There are many different types of techniques suggested
in the literature for extracting unique and invariant feature on rotation, translation and scale. Wavelet techniques
are used in the wide range of problems in extraction, classification, data compression, de-noisingand
reconstruction. Some procedures and techniques used at the output of the wavelet transform to generate a binary
feature vector, while other technique consider real value feature vector as output as a real valued featured vector.
But the ordinary discrete transform is not shift invariant because of the decimal operation during the transform.
Therefore any minor shift in the input signal can cause different output coefficients. DT-CWT has improved
directionality and reduced shift sensitivity and it is approximately invariant. It has real and imaginary part in the
coefficients. The DT-CWT has two real wavelet transform in parallel where the wavelets of one branch are the
other are Hilbert transform of the wavelet. In any high security application, both extremely low falseacceptance
rate FAR and false rejection rate FRR are desirableat the same time this is also called the doublelow problem.
The discrete wavelet transform (DWT) which is commonly used in its maximallydecimated form. This technique
works good for compression of images.Its use for analysis of signal and reconstruction of image tasks has been
hindered by two disadvantages of discrete wavelet transform DWT:
DWT has lack of shift invariancewhich means that a small shift in the incoming signal can causea significant
variation in the distribution of energy of coefficients of DWT at different scales.
For the diagonal features it has poor directional and rotational selectivity, as the filters arereal and
distinguishable.
Shift invariance can be provided by use of the undecimated form ofthe dyadic filter tree compared to the
decimated discrete wavelet transform DWT tree.However, this suffers from increased computationrequirements
compared to the fully decimated discrete wavelet transform DWT and also exhibits high redundancyin the output
characteristics/ features, making successive processing costlyalso.
Dual-tree complex wavelet transform (DT-CWT) has less time complexity as it is more computationally
efficient.When DT-CWT is applied to multi-dimensional signals it has a good directional
sensitivity.Summarizing the properties of DT-CWT:
Approximate shift invariance;
Good directional selectivity in 2-dimension (2-D) like Gabor filter banks.
Perfect reconstruction of the image (PR) using short linearphase filters;
Computational Efficiency.
The complex wavelet methods, analysed here, offer perfect reconstruction,better directional selectivity, and a
general multiscale decomposition.
5. Finger Knuckle Analysis: Gabor Vs DTCWT
International organization of Scientific Research 5 | P a g e
V. RESULTS & DISCUSSIONS
The database for FKP images has been provided by Biometrics Research Center, The Hong Kong
Polytechnic University. The database consists of165 FKP images having images of four fingers and 12 images of
each finger at different ambient lights. Experiments were carried out to appraise the functioning, evaluate and
compare the performanceof both methods. Experimental results verifythat the DT-CWT method can achieve
satisfactoryrecognition in real time. For two techniques, differentfeature extraction result in different
recognitionperformances. Finally, these two systems are compared for the features extraction viz the False
Rejection Rate, False Accept Rate and Equal Error Rates. Experiments are performed to evaluate both the
techniques and capabilities, and experimental results demonstrate that DT-CWT can achieve anencouraging
performance.
Figure 4: Performance of Gabor extraction technique
Figure 5: Performance of DTCWT extraction technique
Comparison Gabor Filter vs Dual Tree Complex Wavelet Transform
DT CWT is less time complex and computationally efficient system produced the following outputs and
allows the transform to provide approximate shiftinvariance anddirectionally selective filters while preserving the
properties of perfect reconstruction and computationalefficiency with good well-balanced frequency responses.
Further the degree of threshold and feature detection capability is more with the Dual tree complex wavelet
transform.
False Reject vs True Accept
The False Reject Vs True Accept graph shows that for a low value of the false reject the standards of true accept
is better for DTCWT technique. This means that the DTCWT system performance is better compared to Gabor
technique.
-10
0
10
20
30
40
50
60
0 10 20 30
Percentage
Threshold
Gabor Filter Performance
False Reject
False Accept
True Accept
True Reject
-20
0
20
40
60
80
0 500 1000
Percentage
Threshold
DTCWT Perfomance
False Reject
False Accept
True Accept
True Reject
6. Finger Knuckle Analysis: Gabor Vs DTCWT
International organization of Scientific Research 6 | P a g e
True Reject vs True Accept
The True Reject Vs True Accept graph shows that for a low value of the false reject, the readings of true
accept is better for DTCWT technique. This means that the DTCWT system performance is better compared to
Gabor technique.
False Accept vs False Reject
The False Accept Vs False Reject graph shows that the false accept of DTCWT is lower than the Gabor System.
Thisanalysis depicts that the DTCWT system performance is better compared to Gabor technique.
0
20
40
60
80
-20 0 20 40 60
TrueAccept
False Reject
Gabor vs DTCWT
Gabor
DTCWT
0
20
40
60
80
-20 0 20 40 60
TrueAccept
True Reject
Gabor vs DTCWT
Gabor
DTCWT
-10
0
10
20
30
40
50
60
-20 0 20 40 60
FalseReject
False Accept
Comparison: Gabor vs DTCWT
Gabor False
Reject
DTCWT False
Reject
7. Finger Knuckle Analysis: Gabor Vs DTCWT
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False Accept vs True Reject
The False Accept Vs True Reject graph shows that the false accept of DTCWT is lower than the Gabor System.
This illustrates that the DTCWT system performance is better compared to Gabor technique.
False Accept vs True Accept
The False Accept Vs True Accept graph shows that the false accept of DTCWT is lower than the Gabor
System and also better True Accept values are obtained for a low FalseAccept in case of DTCWT technique .
This means that the DTCWT system performance is better compared to Gabor technique.
False Accept vs All Values of Gabor and DTCWT
The False Accept Vs other values in the graph shows that the false accept of DTCWT is lower than the Gabor
System and also better True Accept values are obtained for a low False Accept in case of DTCWT technique .
This means that the DTCWT system performance is better compared to Gabor technique.
-10
0
10
20
30
40
50
60
-50 0 50 100
TrueReject
False Accept
Comparison: Gabor vs DTCWT
Gabor True
Reject
DTCWT True
Reject
0
20
40
60
80
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TrueAccept
False Accept
Comparison: Gabor vs DTCWT
Gabor True
Accept
DTCWT True
Accept
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20
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Percentage
False Accept
Comparison: Gabor vs DTCWT
Gabor False
Reject
Gabor True
Reject
8. Finger Knuckle Analysis: Gabor Vs DTCWT
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0 2 4 6 8 10 12 14 16 18 20
0.2
0.25
0.3
0.35
0.4
0.45
0.5
0.55
0.6
0.65
Time Complexity of Gabor and DTCWT
Time Complexity of Gabor and DTCWT in the graph shows that the time required to compute DTCWT features
is 10 times lesser than the Gabor System and also time elapsed to compute is for DTCWT technique is stable
barring the time taken to compute for initial two subjects. This means that the DTCWT system performance is
better compared toGabor.
VI. CONCLUSION AND FUTURE WORK
This paper presented a comparison of two approaches for personal identification using two dimensional
2D finger knuckle image. Feature based approach 2D Gabor filter method and 2DDual tree complex wavelet
transformis used for identification of knuckle based system.2D DT-CWT bases systems for feature extraction and
classification have been quite effective and efficient in achieving high performance in knuckle recognition and
classification. Further, the Dual tree complex wavelet transform Finger Knuckle Identification technique has
several advantages such as less time complexity, computational efficiency, user friendliness, reasonable size and
cost effectiveness. It has a great potential to be improved and employed in real time applications or utilities in
future. This work deliberated single finger knuckle image for identification and classification. In future this can
also be extended by considering multiple finger knuckle images along with bending characteristics. Finger
geometry and knuckle bending information may also be combined and used for person identification. Variations
in the knuckle creases due to some disease or disorder may degrade the performance, which requires further
investigation.
VII. ACKNOWLEDGMENT
I extend my heartfelt thanks to my husband, Jaimandeep Singh, parents in law and my son Prathyush whose
love, patience, and continual support helped me to complete this study.
REFERENCES
[1] G.S Badrinath, Aditya Nigam and Phalguni Gupta, “An Efficient Finger-knuckle-print based Recognition
System Fusing SIFT and SURF Matching Scores” , Proceedings of 13th International Conference on
Information and Communications Security.
[2] Ajay Kumar and Yingbo Zhou, “Personal Identification using Finger Knuckle Orientation Features”,
Electronics Letters Vol. 45, No. 20.
0 2 4 6 8 10 12 14 16 18 20
0.01
0.02
0.03
0.04
0.05
0.06
0.07
0.08
Time Complexity: DTCWT
time
time
Time Complexity: Gabor
Time Complexity: DTCWT
9. Finger Knuckle Analysis: Gabor Vs DTCWT
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[3] Tao Kong, Gongping Yang and Lu Yang, “A hierarchical classification method for finger knuckle print
recognition”, EURASIP Journal on Advances in Signal Processing 2014 http://asp.eurasipjournals.com/
content/2014/1/44
[4] LinlinShen, Li Bai and Zhen Ji, "Hand-based biometrics fusing palmprint and finger knuckle-print"
[5] D. Gabor, Theory of communication, Journal of the Institute of Electrical Engineers 1946; 429-457.
[6] L. Nanni, A. Lumini, On selecting Gabor features for biometric authentication, International Journal of
Computer Applications in Technology.
[7] A. Kong, “An evaluation of Gabor orientation as a feature for face recognition”, Proceedings of ICPR’08.
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Intelligence1996.