This document discusses an iris recognition system that uses Gabor wavelet filters for feature extraction and encoding of iris images. It proposes using 1D Gabor filters to convolve the normalized iris pattern and extract features. A feature vector is formed by phase quantizing the filter outputs. Hamming distance is used as the matching metric to compare iris codes, with distance thresholds set to determine matches. The system aims to accurately identify individuals by encoding the most discriminative iris pattern features while accounting for noise and rotations between 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.
Comparison of Wavelet Watermarking Method With & without Estimator Approachijsrd.com
1. The document compares a wavelet watermarking method with and without an estimator approach for improving robustness against noise attacks.
2. Using an M-estimator at extraction improves imperceptibility and robustness by estimating and rejecting outlier pixels caused by noise.
3. Statistical analysis on watermarked images subjected to noise attacks shows the estimator approach reduces MSE and increases PSNR and correlation, indicating superior extraction quality compared to the standard wavelet method without estimator.
Design of Gabor Filter for Noise Reduction in Betel Vine leaves Disease Segme...IOSR Journals
This document describes a design of a Gabor filter for noise reduction in images of betel vine leaves to aid in disease segmentation. A Gabor filter is designed using Verilog HDL and implemented on a CADENCE platform. The filter takes pixel inputs from images that have undergone preprocessing like Sobel edge detection and segmentation. It convolves the pixels with stored filter coefficients to reduce noise and segment the diseased areas. The proposed Gabor filter achieves noiseless segmentation with increased speed and reduced delays compared to existing methods. It utilizes fewer resources with minimal warnings. The system could be enhanced further with 2D/3D processing and neural network training.
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.
Denoising and Edge Detection Using SobelmethodIJMER
The main aim of our study is to detect edges in the image without any noise , In many of the images edges carry important information of the image, this paper presents a method which consists of sobel operator and discrete wavelet de-noising to do edge detection on images which include white Gaussian noises. There were so many methods for the edge detection, sobel is the one of the method, by using this sobel operator or median filtering, salt and pepper noise cannot be removed properly, so firstly we use complex wavelet to remove noise and sobel operator is used to do edge detection on the image. Through the pictures obtained by the experiment, we can observe that compared to other methods, the method has more obvious effect on edge detection.
A Method of Survey on Object-Oriented Shadow Detection & Removal for High Res...IJERA Editor
High-resolution remote sensing images offer great possibilities for urban mapping. Unfortunately, shadows cast
by buildings during this some problems occurred .This paper mainly focus to get the high resolution colour
remote sensing image, and also undertaken to remove the shaded region in the both urban and rural areas. The
region growing thresholding algorithm is used to detect the shadow and extract the features from shadow region.
Then determine whether those neighbouring pixels are added to the seed points or not. In the region growing
threshold algorithm, Pixels are placed in the region based on their properties or the properties of nearby pixel
values. Then the pixels containing similar properties are grouped together and distributed throughout the image.
IOOPL matching is used for removing shadow from image. This method proves it can remove 80% shaded
region from image efficiently.
Gabor filter is a powerful way to enhance biometric images like fingerprint images in order to extract correct features from these images, Gabor filter used in extracting features directly asin iris images, and sometimes Gabor filter has been used for texture analysis. In fingerprint images The even symmetric Gabor filter is contextual filter or multi-resolution filter will be used to enhance fingerprint imageby filling small gaps (low-pass effect) in the direction of the ridge (black regions) and to increase the discrimination between ridge and valley (black and white regions) in the direction, orthogonal to the ridge, the proposed method in applying Gabor filter on fingerprint images depending on translated fingerprint image into binary image after applying some simple enhancing methods to partially overcome time consuming problem of the Gabor filter.
Secure System based on Dynamic Features of IRIS Recognitionijsrd.com
Basically, the idea behind this system is improvement in cybernetics, the biometric person identification technique based on the pattern of the human iris is well suited to be applied to access control. The human eye is sensitive to visible light. Security systems having realized the value of biometrics for two basic purposes: to verify or identify users. In this busy world, identification should be fast and efficient. In this paper I focus on an efficient methodology for identification and verification for iris detection using Haar transform and Minimum hamming distance. I use canny operator for the edge detection. This biological phenomenon contracts and dilates the two pupils synchronously when illuminating one of the eyes by visible light .I applied the Haar wavelet compressing the data. By comparing the quantized vectors using the Hamming Distance operator, we determine finally whether two irises are similar. The result shows that system is quite effective.
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.
Comparison of Wavelet Watermarking Method With & without Estimator Approachijsrd.com
1. The document compares a wavelet watermarking method with and without an estimator approach for improving robustness against noise attacks.
2. Using an M-estimator at extraction improves imperceptibility and robustness by estimating and rejecting outlier pixels caused by noise.
3. Statistical analysis on watermarked images subjected to noise attacks shows the estimator approach reduces MSE and increases PSNR and correlation, indicating superior extraction quality compared to the standard wavelet method without estimator.
Design of Gabor Filter for Noise Reduction in Betel Vine leaves Disease Segme...IOSR Journals
This document describes a design of a Gabor filter for noise reduction in images of betel vine leaves to aid in disease segmentation. A Gabor filter is designed using Verilog HDL and implemented on a CADENCE platform. The filter takes pixel inputs from images that have undergone preprocessing like Sobel edge detection and segmentation. It convolves the pixels with stored filter coefficients to reduce noise and segment the diseased areas. The proposed Gabor filter achieves noiseless segmentation with increased speed and reduced delays compared to existing methods. It utilizes fewer resources with minimal warnings. The system could be enhanced further with 2D/3D processing and neural network training.
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.
Denoising and Edge Detection Using SobelmethodIJMER
The main aim of our study is to detect edges in the image without any noise , In many of the images edges carry important information of the image, this paper presents a method which consists of sobel operator and discrete wavelet de-noising to do edge detection on images which include white Gaussian noises. There were so many methods for the edge detection, sobel is the one of the method, by using this sobel operator or median filtering, salt and pepper noise cannot be removed properly, so firstly we use complex wavelet to remove noise and sobel operator is used to do edge detection on the image. Through the pictures obtained by the experiment, we can observe that compared to other methods, the method has more obvious effect on edge detection.
A Method of Survey on Object-Oriented Shadow Detection & Removal for High Res...IJERA Editor
High-resolution remote sensing images offer great possibilities for urban mapping. Unfortunately, shadows cast
by buildings during this some problems occurred .This paper mainly focus to get the high resolution colour
remote sensing image, and also undertaken to remove the shaded region in the both urban and rural areas. The
region growing thresholding algorithm is used to detect the shadow and extract the features from shadow region.
Then determine whether those neighbouring pixels are added to the seed points or not. In the region growing
threshold algorithm, Pixels are placed in the region based on their properties or the properties of nearby pixel
values. Then the pixels containing similar properties are grouped together and distributed throughout the image.
IOOPL matching is used for removing shadow from image. This method proves it can remove 80% shaded
region from image efficiently.
Gabor filter is a powerful way to enhance biometric images like fingerprint images in order to extract correct features from these images, Gabor filter used in extracting features directly asin iris images, and sometimes Gabor filter has been used for texture analysis. In fingerprint images The even symmetric Gabor filter is contextual filter or multi-resolution filter will be used to enhance fingerprint imageby filling small gaps (low-pass effect) in the direction of the ridge (black regions) and to increase the discrimination between ridge and valley (black and white regions) in the direction, orthogonal to the ridge, the proposed method in applying Gabor filter on fingerprint images depending on translated fingerprint image into binary image after applying some simple enhancing methods to partially overcome time consuming problem of the Gabor filter.
Secure System based on Dynamic Features of IRIS Recognitionijsrd.com
Basically, the idea behind this system is improvement in cybernetics, the biometric person identification technique based on the pattern of the human iris is well suited to be applied to access control. The human eye is sensitive to visible light. Security systems having realized the value of biometrics for two basic purposes: to verify or identify users. In this busy world, identification should be fast and efficient. In this paper I focus on an efficient methodology for identification and verification for iris detection using Haar transform and Minimum hamming distance. I use canny operator for the edge detection. This biological phenomenon contracts and dilates the two pupils synchronously when illuminating one of the eyes by visible light .I applied the Haar wavelet compressing the data. By comparing the quantized vectors using the Hamming Distance operator, we determine finally whether two irises are similar. The result shows that system is quite effective.
Edge detection of herbal plants is a set of mathematical methods which aim at identifying points in a digital image at which the image brightness changes sharply and has discontinuities. They are defined as the set of curved line segments termed edges. Effective edge detection for microscopic image of herbal plant is proposed through this paper which compares the edge detected images and then performs further segmentation. Comparison between Sobel operator, Prewitt, Canny and Robert cross operators is performed. Our method after efficient edge detection performs Gabor filter and K-means clustering to procure a better image. It is then subjected to further segmentation. Experimental methods in our proposed algorithm show that our method achieves a better edge detection as compared to other edge detector operators. Our proposed algorithm provides the maximum PSNR value of 43.684 amongst the other commercial edge detection operators.
This document discusses a hand gesture recognition system for underprivileged individuals. It begins by outlining the key steps in hand gesture recognition systems: image capture, pre-processing, segmentation, feature extraction and gesture recognition. It then goes into more detail on specific techniques for each step, such as thresholding and edge detection for segmentation. The document also covers applications like access control, sign language translation and future areas like biometric authentication. In conclusion, it proposes that hand gesture recognition can help disabled individuals communicate through accessible human-computer interaction.
The document summarizes several popular iris recognition algorithms: Daugman, Li Ma, Wildes, and Tisse. It describes the key steps and approaches for each algorithm: segmentation, normalization, feature extraction, and matching. It finds Daugman's algorithm to be the most accurate according to tests on the CASIA iris image database, with 0.01/0.09 FAR/FRR and 99.90% accuracy. The document provides references for further reading on iris recognition and the algorithms discussed.
A Comparative Study of Image Denoising Techniques for Medical ImagesIRJET Journal
This document discusses image denoising techniques for medical images. It begins by introducing how medical images are used for disease diagnosis but the image acquisition process can introduce noise. The goal of image denoising is to remove noise while preserving image details. Different types of noise that affect medical images are described such as Gaussian, salt and pepper, and speckle noise. Denoising techniques are categorized as operating in the spatial domain using filters like mean, median, and adaptive median filters, or in the transform domain using wavelet thresholding. Performance is measured using metrics like peak signal-to-noise ratio and mean squared error. In conclusion, transform domain filtering with wavelets is effective due to properties like sparsity and multi-
This document summarizes a research paper that proposes a new method for finger image identification using score-level fusion of finger vein and fingerprint images. The proposed system captures finger vein and low-resolution fingerprint images simultaneously and combines them using a novel score-level fusion strategy. This approach is found to have better identification performance than existing finger vein-only methods. The paper develops and evaluates two new score-level combination methods called holistic and nonlinear fusion, and finds they outperform other popular score-level fusion approaches. Preprocessing, feature extraction using Gabor filters, and score-level matching steps are described for both finger vein and fingerprint identification. Experimental results on a large database suggest the proposed multimodal approach has significantly improved identification accuracy over
Performance evaluation of lossy image compression techniques over an awgn cha...eSAT Journals
Abstract Recent advancement in image compression research resulted in reducing the time and cost in image storage and transmission without significant reduction of the image quality. In this paper software algorithms for image compression based on psycho visual and inter pixel redundancy elimination have been developed and implemented. This paper examines the suitability of these two compression techniques over a practical AWGN communication channel and concludes with an experimental comparison on the basis of BER v/s Eb/No ratio. Key Words: Psycho visual redundancy, inter pixel redundancy, lossless and lossy compression, AWGN channel, BER, Eb/No ratio.
A New Technique of Extraction of Edge Detection Using Digital Image Processing IJMER
Digital image Processing is one of the basic and important tool in the image processing and
computer vision. In this paper we discuss about the extraction of a digital image edge using different
digital image processing techniques. Edge detection is the most common technique for detecting
discontinuities in intensity values. The input image or actual image have some noise that may cause the
of quality of the digital image. Firstly, wavelet transform is used to remove noises from the image
collected. Secondly, some edge detection operators such as Differential edge detection, Log edge
detection, canny edge detection and Binary morphology are analyzed. And then according to the
simulation results, the advantages and disadvantages of these edge detection operators are compared. It
is shown that the Binary morphology operator can obtain better edge feature. Finally, in order to gain
clear and integral image profile, the method of ordering closed is given. After experimentation, edge
detection method proposed in this paper is feasible.
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.
AN EMERGING TREND OF FEATURE EXTRACTION METHOD IN VIDEO PROCESSINGcscpconf
Recently the progress in technology and flourishing applications open up new forecast and defy
for the image and video processing community. Compared to still images, video sequences
afford more information about how objects and scenarios change over time. Quality of video is
very significant before applying it to any kind of processing techniques. This paper deals with
two major problems in video processing they are noise reduction and object segmentation on
video frames. The segmentation of objects is performed using foreground segmentation based
and fuzzy c-means clustering segmentation is compared with the proposed method Improvised
fuzzy c – means segmentation based on color. This was applied in the video frame to segment
various objects in the current frame. The proposed technique is a powerful method for image
segmentation and it works for both single and multiple feature data with spatial information.
The experimental result was conducted using various noises and filtering methods to show which is best suited among others and the proposed segmentation approach generates good quality segmented frames.
This document describes iris and periocular recognition techniques. It discusses segmentation, normalization, feature extraction and matching steps for iris recognition. Segmentation involves localization of the iris and eyelid detection. Normalization maps the iris to polar coordinates. Features are represented as a 2048-bit iris code. Periocular recognition uses the area around the eye for identification. The document tests the techniques on three datasets, achieving 100% accuracy even with noise, blur and transformations added to query images. Processing time increases with the number of keypoints and image size.
Efficient fingerprint image enhancement algorithm based on gabor filtereSAT Publishing House
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
GABOR WAVELETS AND MORPHOLOGICAL SHARED WEIGHTED NEURAL NETWORK BASED AUTOMAT...sipij
1) The document proposes an automatic face recognition system using Gabor wavelet face detection with neural networks and morphological shared weighted neural networks (MSNN) for face recognition.
2) Face detection is performed using Gabor filters for feature extraction and a neural network for classification. Detected faces are input to the MSNN for face recognition.
3) The MSNN uses hit-miss transforms for feature extraction in each layer, which are independent of grayscale shifts. Feature matching compares output thresholds to identify faces.
This paper proposes a method for image denoising using wavelet thresholding while preserving edge information. It first detects edges in the noisy image using Canny edge detection. It then applies a wavelet transform and thresholds the coefficients, preserving values near detected edges. Two thresholding methods are discussed: Visushrink for sparse images and Sureshrink for others. The inverse wavelet transform is applied to obtain the denoised image with preserved edges. The goal is to remove noise while maintaining important image features like edges. The method is described to provide better denoising than alternatives that oversmooth edges.
Fpga implementation of image segmentation by using edge detection based on so...eSAT Journals
This document summarizes an article that presents a method for implementing image segmentation using edge detection based on the Sobel edge operator on an FPGA. It describes how the Sobel operator works by calculating horizontal and vertical gradients to detect edges. The document outlines the steps to segment an image using Sobel edge detection, including applying horizontal and vertical masks, calculating the gradient, and thresholding. It also provides the architecture for the FPGA implementation, including modules for pixel generation, Sobel enhancement, edge detection, and binary segmentation. The results show edge detection outputs from MATLAB and simulation waveforms, demonstrating the FPGA-based method can perform edge-based image segmentation.
Fpga implementation of image segmentation by using edge detection based on so...eSAT Publishing House
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.
Fingerprint image enhancement is the key process in IAFIS systems. In order to reduce false identification ratio and to supply good fingerprint images to IAFIS systems for exact identification, fingerprint images are generally enhanced. A filtering process tries to filter out the noise from the input image, and emphasize on low, high and directional spatial frequency components of an image. This paper presents an experimental summary of enhancing fingerprint images using Gabor filters. Frequency, width and window domain filter ranges are fixed. The orientation angle alone is modified by 0 radians, π/2, π/4 and 3π/4 radians. The experimental results show that Gabor filter enhances the fingerprint image in a better way than other filtering methods and extracts features.
14 offline signature verification based on euclidean distance using support v...INFOGAIN PUBLICATION
In this project, a support vector machine is developed for identity verification of offline signature based on the matrices derived through Euclidean distance. A set of signature samples are collected from 35 different people. Each person gives his 15 different copies of signature and then these signature samples are scanned to have softcopy of them to train SVM. These scanned signature images are then subjected to a number of image enhancement operations like binarization, complementation, filtering, thinning, edge detection and rotation. On the basis of 15 original signature copies from each individual, Euclidean distance is calculated. And every tested image is compared with the range of Euclidean distance. The values from the ED are fed to the support vector machine which draws a hyper plane and classifies the signature into original or forged based on a particular feature value.
The document presents a novel method for character segmentation of vehicle license plates written in two rows. It discusses how the license plate image is first preprocessed through steps like grayscale conversion, binarization, and noise removal. Horizontal and vertical projections are then used to segment the image into lines and words. Character segmentation is done by analyzing the spacing between characters. Finally, zone segmentation is performed to divide each character into four zones to extract features for recognition. The method aims to simplify license plate image analysis for applications like traffic monitoring and surveillance.
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.
Shadow Detection and Removal Techniques A Perspective Viewijtsrd
This document discusses techniques for shadow detection and removal in images. It provides an overview of various methods used, including those based on texture analysis, color information, Gaussian mixture models, and deterministic non-model based approaches. The document then reviews several published papers on different shadow detection and removal algorithms. These algorithms are compared based on advantages and disadvantages in terms of accuracy, computational efficiency, and applicability to different image types and conditions. The conclusion is that shadows remain a challenging problem for computer vision tasks and that the most suitable detection and removal technique depends on the specific image type and application.
This document summarizes various methods for iris feature extraction that are used in iris recognition systems. It discusses four main categories of iris feature extraction techniques: texture-based, phase-based, zero-crossing based, and intensity variation based. It provides details on several popular methods, including Gabor filtering, Log-Gabor filtering, wavelet transforms, and Haar encoding. It also reviews several studies that have compared the performance of different iris feature extraction algorithms and their accuracy rates.
AN IMPROVED IRIS RECOGNITION SYSTEM BASED ON 2-D DCT AND HAMMING DISTANCE TEC...IJEEE
This paper proposes a new iris recognition system that implements Integro-Differential, Daugman Rubber Sheet Model, 2-D DCT, Hamming Distance to exact features from the iris and matching it with the sorted database.All these image-processing algorithms have been validated on noised real iris images & UBIRIS database
Edge detection of herbal plants is a set of mathematical methods which aim at identifying points in a digital image at which the image brightness changes sharply and has discontinuities. They are defined as the set of curved line segments termed edges. Effective edge detection for microscopic image of herbal plant is proposed through this paper which compares the edge detected images and then performs further segmentation. Comparison between Sobel operator, Prewitt, Canny and Robert cross operators is performed. Our method after efficient edge detection performs Gabor filter and K-means clustering to procure a better image. It is then subjected to further segmentation. Experimental methods in our proposed algorithm show that our method achieves a better edge detection as compared to other edge detector operators. Our proposed algorithm provides the maximum PSNR value of 43.684 amongst the other commercial edge detection operators.
This document discusses a hand gesture recognition system for underprivileged individuals. It begins by outlining the key steps in hand gesture recognition systems: image capture, pre-processing, segmentation, feature extraction and gesture recognition. It then goes into more detail on specific techniques for each step, such as thresholding and edge detection for segmentation. The document also covers applications like access control, sign language translation and future areas like biometric authentication. In conclusion, it proposes that hand gesture recognition can help disabled individuals communicate through accessible human-computer interaction.
The document summarizes several popular iris recognition algorithms: Daugman, Li Ma, Wildes, and Tisse. It describes the key steps and approaches for each algorithm: segmentation, normalization, feature extraction, and matching. It finds Daugman's algorithm to be the most accurate according to tests on the CASIA iris image database, with 0.01/0.09 FAR/FRR and 99.90% accuracy. The document provides references for further reading on iris recognition and the algorithms discussed.
A Comparative Study of Image Denoising Techniques for Medical ImagesIRJET Journal
This document discusses image denoising techniques for medical images. It begins by introducing how medical images are used for disease diagnosis but the image acquisition process can introduce noise. The goal of image denoising is to remove noise while preserving image details. Different types of noise that affect medical images are described such as Gaussian, salt and pepper, and speckle noise. Denoising techniques are categorized as operating in the spatial domain using filters like mean, median, and adaptive median filters, or in the transform domain using wavelet thresholding. Performance is measured using metrics like peak signal-to-noise ratio and mean squared error. In conclusion, transform domain filtering with wavelets is effective due to properties like sparsity and multi-
This document summarizes a research paper that proposes a new method for finger image identification using score-level fusion of finger vein and fingerprint images. The proposed system captures finger vein and low-resolution fingerprint images simultaneously and combines them using a novel score-level fusion strategy. This approach is found to have better identification performance than existing finger vein-only methods. The paper develops and evaluates two new score-level combination methods called holistic and nonlinear fusion, and finds they outperform other popular score-level fusion approaches. Preprocessing, feature extraction using Gabor filters, and score-level matching steps are described for both finger vein and fingerprint identification. Experimental results on a large database suggest the proposed multimodal approach has significantly improved identification accuracy over
Performance evaluation of lossy image compression techniques over an awgn cha...eSAT Journals
Abstract Recent advancement in image compression research resulted in reducing the time and cost in image storage and transmission without significant reduction of the image quality. In this paper software algorithms for image compression based on psycho visual and inter pixel redundancy elimination have been developed and implemented. This paper examines the suitability of these two compression techniques over a practical AWGN communication channel and concludes with an experimental comparison on the basis of BER v/s Eb/No ratio. Key Words: Psycho visual redundancy, inter pixel redundancy, lossless and lossy compression, AWGN channel, BER, Eb/No ratio.
A New Technique of Extraction of Edge Detection Using Digital Image Processing IJMER
Digital image Processing is one of the basic and important tool in the image processing and
computer vision. In this paper we discuss about the extraction of a digital image edge using different
digital image processing techniques. Edge detection is the most common technique for detecting
discontinuities in intensity values. The input image or actual image have some noise that may cause the
of quality of the digital image. Firstly, wavelet transform is used to remove noises from the image
collected. Secondly, some edge detection operators such as Differential edge detection, Log edge
detection, canny edge detection and Binary morphology are analyzed. And then according to the
simulation results, the advantages and disadvantages of these edge detection operators are compared. It
is shown that the Binary morphology operator can obtain better edge feature. Finally, in order to gain
clear and integral image profile, the method of ordering closed is given. After experimentation, edge
detection method proposed in this paper is feasible.
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.
AN EMERGING TREND OF FEATURE EXTRACTION METHOD IN VIDEO PROCESSINGcscpconf
Recently the progress in technology and flourishing applications open up new forecast and defy
for the image and video processing community. Compared to still images, video sequences
afford more information about how objects and scenarios change over time. Quality of video is
very significant before applying it to any kind of processing techniques. This paper deals with
two major problems in video processing they are noise reduction and object segmentation on
video frames. The segmentation of objects is performed using foreground segmentation based
and fuzzy c-means clustering segmentation is compared with the proposed method Improvised
fuzzy c – means segmentation based on color. This was applied in the video frame to segment
various objects in the current frame. The proposed technique is a powerful method for image
segmentation and it works for both single and multiple feature data with spatial information.
The experimental result was conducted using various noises and filtering methods to show which is best suited among others and the proposed segmentation approach generates good quality segmented frames.
This document describes iris and periocular recognition techniques. It discusses segmentation, normalization, feature extraction and matching steps for iris recognition. Segmentation involves localization of the iris and eyelid detection. Normalization maps the iris to polar coordinates. Features are represented as a 2048-bit iris code. Periocular recognition uses the area around the eye for identification. The document tests the techniques on three datasets, achieving 100% accuracy even with noise, blur and transformations added to query images. Processing time increases with the number of keypoints and image size.
Efficient fingerprint image enhancement algorithm based on gabor filtereSAT Publishing House
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
GABOR WAVELETS AND MORPHOLOGICAL SHARED WEIGHTED NEURAL NETWORK BASED AUTOMAT...sipij
1) The document proposes an automatic face recognition system using Gabor wavelet face detection with neural networks and morphological shared weighted neural networks (MSNN) for face recognition.
2) Face detection is performed using Gabor filters for feature extraction and a neural network for classification. Detected faces are input to the MSNN for face recognition.
3) The MSNN uses hit-miss transforms for feature extraction in each layer, which are independent of grayscale shifts. Feature matching compares output thresholds to identify faces.
This paper proposes a method for image denoising using wavelet thresholding while preserving edge information. It first detects edges in the noisy image using Canny edge detection. It then applies a wavelet transform and thresholds the coefficients, preserving values near detected edges. Two thresholding methods are discussed: Visushrink for sparse images and Sureshrink for others. The inverse wavelet transform is applied to obtain the denoised image with preserved edges. The goal is to remove noise while maintaining important image features like edges. The method is described to provide better denoising than alternatives that oversmooth edges.
Fpga implementation of image segmentation by using edge detection based on so...eSAT Journals
This document summarizes an article that presents a method for implementing image segmentation using edge detection based on the Sobel edge operator on an FPGA. It describes how the Sobel operator works by calculating horizontal and vertical gradients to detect edges. The document outlines the steps to segment an image using Sobel edge detection, including applying horizontal and vertical masks, calculating the gradient, and thresholding. It also provides the architecture for the FPGA implementation, including modules for pixel generation, Sobel enhancement, edge detection, and binary segmentation. The results show edge detection outputs from MATLAB and simulation waveforms, demonstrating the FPGA-based method can perform edge-based image segmentation.
Fpga implementation of image segmentation by using edge detection based on so...eSAT Publishing House
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.
Fingerprint image enhancement is the key process in IAFIS systems. In order to reduce false identification ratio and to supply good fingerprint images to IAFIS systems for exact identification, fingerprint images are generally enhanced. A filtering process tries to filter out the noise from the input image, and emphasize on low, high and directional spatial frequency components of an image. This paper presents an experimental summary of enhancing fingerprint images using Gabor filters. Frequency, width and window domain filter ranges are fixed. The orientation angle alone is modified by 0 radians, π/2, π/4 and 3π/4 radians. The experimental results show that Gabor filter enhances the fingerprint image in a better way than other filtering methods and extracts features.
14 offline signature verification based on euclidean distance using support v...INFOGAIN PUBLICATION
In this project, a support vector machine is developed for identity verification of offline signature based on the matrices derived through Euclidean distance. A set of signature samples are collected from 35 different people. Each person gives his 15 different copies of signature and then these signature samples are scanned to have softcopy of them to train SVM. These scanned signature images are then subjected to a number of image enhancement operations like binarization, complementation, filtering, thinning, edge detection and rotation. On the basis of 15 original signature copies from each individual, Euclidean distance is calculated. And every tested image is compared with the range of Euclidean distance. The values from the ED are fed to the support vector machine which draws a hyper plane and classifies the signature into original or forged based on a particular feature value.
The document presents a novel method for character segmentation of vehicle license plates written in two rows. It discusses how the license plate image is first preprocessed through steps like grayscale conversion, binarization, and noise removal. Horizontal and vertical projections are then used to segment the image into lines and words. Character segmentation is done by analyzing the spacing between characters. Finally, zone segmentation is performed to divide each character into four zones to extract features for recognition. The method aims to simplify license plate image analysis for applications like traffic monitoring and surveillance.
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.
Shadow Detection and Removal Techniques A Perspective Viewijtsrd
This document discusses techniques for shadow detection and removal in images. It provides an overview of various methods used, including those based on texture analysis, color information, Gaussian mixture models, and deterministic non-model based approaches. The document then reviews several published papers on different shadow detection and removal algorithms. These algorithms are compared based on advantages and disadvantages in terms of accuracy, computational efficiency, and applicability to different image types and conditions. The conclusion is that shadows remain a challenging problem for computer vision tasks and that the most suitable detection and removal technique depends on the specific image type and application.
This document summarizes various methods for iris feature extraction that are used in iris recognition systems. It discusses four main categories of iris feature extraction techniques: texture-based, phase-based, zero-crossing based, and intensity variation based. It provides details on several popular methods, including Gabor filtering, Log-Gabor filtering, wavelet transforms, and Haar encoding. It also reviews several studies that have compared the performance of different iris feature extraction algorithms and their accuracy rates.
AN IMPROVED IRIS RECOGNITION SYSTEM BASED ON 2-D DCT AND HAMMING DISTANCE TEC...IJEEE
This paper proposes a new iris recognition system that implements Integro-Differential, Daugman Rubber Sheet Model, 2-D DCT, Hamming Distance to exact features from the iris and matching it with the sorted database.All these image-processing algorithms have been validated on noised real iris images & UBIRIS database
Tonsillitis is a disease that can be found in every
part of the world. Moreover, it is one of the main causes
intervening for heart attack and pneumonia. It has been reported
that there are a large number of people having died because of
heart attack and pneumonia. To improve data transfer rates, this
paper proposes Gabor filter design with efficient noise reduction
and less power consumption usage is proposed in this paper.
Using textural properties of anatomical structures the filter
design is suitable for detecting the early stages of disease. The
code for Gabor filter will be developed in MATLAB
A New Approach of Iris Detection and RecognitionIJECEIAES
This paper proposes an IRIS recognition and detection model for measuring the e-security. This proposed model consists of the following blocks: segmentation and normalization, feature encoding and feature extraction, and classification. In first phase, histogram equalization and canny edge detection is used for object detection. And then, Hough Transformation is utilized for detecting the center of the pupil of an IRIS. In second phase, Daugmen’s Rubber Sheet model and Log Gabor filter is used for normalization and encoding and as a feature extraction method GNS (Global Neighborhood Structure) map is used, finally extracted feature of GNS is feed to the SVM (Support Vector Machine) for training and testing. For our tested dataset, experimental results demonstrate 92% accuracy in real portion and 86% accuracy in imaginary portion for both eyes. In addition, our proposed model outperforms than other two conventional methods exhibiting higher accuracy.
Mislaid character analysis using 2-dimensional discrete wavelet transform for...IJMER
International Journal of Modern Engineering Research (IJMER) is Peer reviewed, online Journal. It serves as an international archival forum of scholarly research related to engineering and science education.
This document summarizes an analysis of iris recognition based on false acceptance rate (FAR) and false rejection rate (FRR) using the Hough transform. It first provides an overview of iris recognition and its typical stages: image acquisition, localization/segmentation, normalization, feature extraction, and pattern matching. It then describes existing methods used in each stage, including the Hough transform and rubber sheet model for localization and normalization. The proposed methodology applies Canny edge detection, Hough transform for boundary detection, normalization with the rubber sheet model, and calculates metrics like mean squared error, root mean squared error, signal-to-noise ratio, and root signal-to-noise ratio to evaluate the accuracy of iris recognition using FAR
This document provides an overview of iris recognition technology. It discusses what the iris is, why it is useful for biometric identification, the history and applications of iris recognition. It then describes the main steps in an iris recognition system: image acquisition, segmentation, normalization, feature encoding, matching. It discusses some common feature encoding and matching methods. In conclusion, iris recognition is considered the most accurate biometric technology due to the iris's complex patterns and stability over time.
This document discusses a novel technique for better analysis of ice properties using Kalman filtering. It summarizes previous research on sea ice segmentation using SAR imagery and dual polarization techniques. It proposes using an automated SAR algorithm along with Kalman filtering to more accurately detect sea ice properties from RADARSAT1 and RADARSAT2 imagery data. The document reviews techniques for image segmentation, dual polarization, PMA detection, and related work on sea ice classification using statistical ice properties, edge preserving region models, and object extraction methods.
This document summarizes a method for enhancing fingerprint images using short-time Fourier transform (STFT) analysis. The key steps are:
1. Performing STFT analysis on overlapping windows of the fingerprint image to estimate the local ridge orientation, frequency, and region mask in each window.
2. Using the estimated orientation and frequency values to filter each window of the fingerprint image in the Fourier domain for enhancement.
3. Reconstructing the enhanced fingerprint image by combining the results from each analyzed window.
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.
This document summarizes a novel approach for iris recognition. It begins by discussing image pre-processing, which includes segmentation of the iris using Daugman's integro-differential operator. This locates the inner and outer boundaries of the iris. Next, normalization is performed using Daugman's rubber sheet model to map the iris region to polar coordinates. Finally, two iris codes are compared using Hamming distance to determine if they match. The proposed method achieves high accuracy for iris recognition with low false acceptance and rejection rates compared to existing algorithms.
IRJET- Advanced Character based Recognition and Phone Handling for Blind ...IRJET Journal
This document describes a system to help blind people by converting text to speech. It uses a Raspberry Pi with a USB camera to scan documents and images. Optical character recognition (OCR) is used to convert the images to digital text. For English text, Tesseract OCR is used, while Tamil text uses segmentation to identify characters. The text is then converted to synthesized speech. Gyroscope sensors also allow blind users to make phone calls by detecting gestures near the sensors. The system aims to make life more independent for blind people.
International Journal of Engineering Research and Applications (IJERA) is a team of researchers not publication services or private publications running the journals for monetary benefits, we are association of scientists and academia who focus only on supporting authors who want to publish their work. The articles published in our journal can be accessed online, all the articles will be archived for real time access.
Our journal system primarily aims to bring out the research talent and the works done by sciaentists, academia, engineers, practitioners, scholars, post graduate students of engineering and science. This journal aims to cover the scientific research in a broader sense and not publishing a niche area of research facilitating researchers from various verticals to publish their papers. It is also aimed to provide a platform for the researchers to publish in a shorter of time, enabling them to continue further All articles published are freely available to scientific researchers in the Government agencies,educators and the general public. We are taking serious efforts to promote our journal across the globe in various ways, we are sure that our journal will act as a scientific platform for all researchers to publish their works online.
IRIS BIOMETRIC RECOGNITION SYSTEM EMPLOYING CANNY OPERATORcsitconf
Biometrics has become important in security applications. In comparison with many other
biometric features, iris recognition has very high recognition accuracy because it depends on
iris which is located in a place that still stable throughout human life and the probability to find
two identical iris's is close to zero. The identification system consists of several stages including
segmentation stage which is the most serious and critical one. The current segmentation
methods still have limitation in localizing the iris due to circular shape consideration of the
pupil. In this research, Daugman method is done to investigate the segmentation techniques.
Eyelid detection is another step that has been included in this study as a part of segmentation
stage to localize the iris accurately and remove unwanted area that might be included. The
obtained iris region is encoded using haar wavelets to construct the iris code, which contains
the most discriminating feature in the iris pattern. Hamming distance is used for comparison of
iris templates in the recognition stage. The dataset which is used for the study is UBIRIS
database. A comparative study of different edge detector operator is performed. It is observed
that canny operator is best suited to extract most of the edges to generate the iris code for
comparison. Recognition rate of 89% and rejection rate of 95% is achieved.
IRIS BIOMETRIC RECOGNITION SYSTEM EMPLOYING CANNY OPERATORcscpconf
Biometrics has become important in security applications. In comparison with many other biometric features, iris recognition has very high recognition accuracy because it depends on
iris which is located in a place that still stable throughout human life and the probability to find two identical iris's is close to zero. The identification system consists of several stages including
segmentation stage which is the most serious and critical one. The current segmentation methods still have limitation in localizing the iris due to circular shape consideration of the
pupil. In this research, Daugman method is done to investigate the segmentation techniques. Eyelid detection is another step that has been included in this study as a part of segmentation
stage to localize the iris accurately and remove unwanted area that might be included. The obtained iris region is encoded using haar wavelets to construct the iris code, which contains
the most discriminating feature in the iris pattern. Hamming distance is used for comparison of iris templates in the recognition stage. The dataset which is used for the study is UBIRIS database. A comparative study of different edge detector operator is performed. It is observed that canny operator is best suited to extract most of the edges to generate the iris code for comparison. Recognition rate of 89% and rejection rate of 95% is achieved.
The document reviews techniques for reducing speckle noise in synthetic aperture radar (SAR) data. It begins by describing the characteristics of speckle noise and its multiplicative nature. It then discusses common spatial domain filtering techniques for SAR data denoising, including Lee filtering, Frost filtering, and Kuan filtering. These are adaptive filters that estimate pixel values based on statistics within a moving window. The document also reviews wavelet-based denoising techniques and their advantages over spatial domain filters, including better preservation of edges. Finally, it provides an overview of future research opportunities in developing new speckle reduction methods.
VHDL Design for Image Segmentation using Gabor filter for Disease DetectionVLSICS Design
Tonsillitis, Tumor and many more skin diseases can be detected in its early-state and can be cured. For this a new idea for efficient Gabor filter design with improved data transfer rate, efficient noise reduction, less power consumption and reduced memory usage is proposed in this paper. The filter design is suitable for detecting the early stages of disease using textural properties of anatomical structures. The code for Gabor filter will be developed in VHDL using Modelsim and then implemented on SPARTAN-3E FPGA kit. These systems must provide both highly accurate and extremely fast processing of large amounts of image data.
Surface generation from point cloud.pdfssuserd3982b1
This document summarizes research on generating 3D surface models from point clouds acquired using a vision-based laser scanning sensor. It discusses using adaptive filters to reduce noise in the point clouds and generating triangular meshes from the point clouds to create an initial surface model. It then covers using NURBS (Non-Uniform Rational B-Splines) to optimize the surface model for accuracy by fitting parametric surfaces to the triangular mesh. The goal is to develop accurate 3D surface models of turbine blades for robotic welding applications to repair flaws.
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 %.
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.
Electrically small antennas: The art of miniaturizationEditor IJARCET
We are living in the technological era, were we preferred to have the portable devices rather than unmovable devices. We are isolating our self rom the wires and we are becoming the habitual of wireless world what makes the device portable? I guess physical dimensions (mechanical) of that particular device, but along with this the electrical dimension is of the device is also of great importance. Reducing the physical dimension of the antenna would result in the small antenna but not electrically small antenna. We have different definition for the electrically small antenna but the one which is most appropriate is, where k is the wave number and is equal to and a is the radius of the imaginary sphere circumscribing the maximum dimension of the antenna. As the present day electronic devices progress to diminish in size, technocrats have become increasingly concentrated on electrically small antenna (ESA) designs to reduce the size of the antenna in the overall electronics system. Researchers in many fields, including RF and Microwave, biomedical technology and national intelligence, can benefit from electrically small antennas as long as the performance of the designed ESA meets the system requirement.
This document provides a comparative study of two-way finite automata and Turing machines. Some key points:
- Two-way finite automata are similar to read-only Turing machines in that they have a finite tape that can be read in both directions, but cannot write to the tape.
- Turing machines have an infinite tape that can be read from and written to, allowing them to recognize recursively enumerable languages.
- Both models are examined in their ability to accept the regular language L={anbm|m,n>0}.
- The time complexity of a two-way finite automaton for this language is O(n2) due to making two passes over the
This document analyzes and compares the performance of the AODV and DSDV routing protocols in a vehicular ad hoc network (VANET) simulation. Simulations were conducted using NS-2, SUMO, and MOVE simulators for a grid map scenario with varying numbers of nodes. The results show that AODV performed better than DSDV in terms of throughput and packet delivery fraction, while DSDV had lower end-to-end delays. However, neither protocol was found to be fully suitable for the highly dynamic VANET environment. The document concludes that further work is needed to develop improved routing protocols optimized for VANETs.
This document discusses the digital circuit layout problem and approaches to solving it using graph partitioning techniques. It begins by introducing the digital circuit layout problem and how it has become more complex with increasing circuit sizes. It then discusses how the problem can be decomposed into subproblems using graph partitioning to assign geometric coordinates to circuit components. The document reviews several traditional approaches to solve the problem, such as the Kernighan-Lin algorithm, and discusses their limitations for larger circuit sizes. It also discusses more recent approaches using evolutionary algorithms and concludes by analyzing the contributions of various approaches.
This document summarizes various data mining techniques that have been used for intrusion detection systems. It first describes the architecture of a data mining-based IDS, including sensors to collect data, detectors to evaluate the data using detection models, a data warehouse for storage, and a model generator. It then discusses supervised and unsupervised learning approaches that have been applied, including neural networks, support vector machines, K-means clustering, and self-organizing maps. Finally, it reviews several related works applying these techniques and compares their results, finding that combinations of approaches can improve detection rates while reducing false alarms.
This document provides an overview of speech recognition systems and recent progress in the field. It discusses different types of speech recognition including isolated word, connected word, continuous speech, and spontaneous speech. Various techniques used in speech recognition are also summarized, such as simulated evolutionary computation, artificial neural networks, fuzzy logic, Kalman filters, and Hidden Markov Models. The document reviews several papers published between 2004-2012 that studied speech recognition methods including using dynamic spectral subband centroids, Kalman filters, biomimetic computing techniques, noise estimation, and modulation filtering. It concludes that Hidden Markov Models combined with MFCC features provide good recognition results for large vocabulary, speaker-independent, continuous speech recognition.
This document discusses integrating two assembly lines, Line A and Line B, based on lean line design concepts to reduce space and operators. It analyzes the current state of the lines using tools like takt time analysis and MTM/UAS studies. Improvements are identified to eliminate waste, including methods improvements, workplace rearrangement, ergonomic changes, and outsourcing. Paper kaizen is conducted and work elements are retimed. The goal is to integrate the lines to better utilize space and manpower while meeting manufacturing standards.
This document summarizes research on the exposure of microwaves from cellular networks. It describes how microwaves interact with biological systems and discusses measurement techniques and safety standards regarding microwave exposure. While some studies have alleged health hazards from microwaves, independent reviews by health organizations have found no evidence that exposure to microwaves below international safety limits causes harm. The document concludes that with precautions like limiting exposure time and using phones with lower SAR ratings, microwaves from cell phones pose minimal health risks.
This document summarizes a research paper that examines the effect of feature reduction in sentiment analysis of online reviews. It uses principle component analysis to reduce the number of features (product attributes) from a dataset of 500 camera reviews labeled as positive or negative. Two models are developed - one using the original set of 95 product attributes, and one using the reduced set. Support vector machines and naive Bayes classifiers are applied to both models and their performance is evaluated to determine if classification accuracy can be maintained while using fewer features. The results show it is possible to achieve similar accuracy levels with less features, improving computational efficiency.
This document provides a review of multispectral palm image fusion techniques. It begins with an introduction to biometrics and palm print identification. Different palm print images capture different spectral information about the palm. The document then reviews several pixel-level fusion methods for combining multispectral palm images, finding that Curvelet transform performs best at preserving discriminative patterns. It also discusses hardware for capturing multispectral palm images and the process of region of interest extraction and localization. Common fusion methods like wavelet transform and Curvelet transform are also summarized.
This document describes a vehicle theft detection system that uses radio frequency identification (RFID) technology. The system involves embedding an RFID chip in each vehicle that continuously transmits a unique identification signal. When a vehicle is stolen, the owner reports it to the police, who upload the vehicle's information to a central database. Police vehicles are equipped with RFID receivers. If a stolen vehicle passes within range of a receiver, the receiver detects the vehicle's ID signal and displays its details on a tablet. This allows police to quickly identify and recover stolen vehicles. The system aims to make it difficult for thieves to hide a vehicle's identity and allows vehicles to be tracked globally wherever the detection system is implemented.
This document discusses and compares two techniques for image denoising using wavelet transforms: Dual-Tree Complex DWT and Double-Density Dual-Tree Complex DWT. Both techniques decompose an image corrupted by noise using filter banks, apply thresholding to the wavelet coefficients, and reconstruct the image. The Double-Density Dual-Tree Complex DWT yields better denoising results than the Dual-Tree Complex DWT as it produces more directional wavelets and is less sensitive to shifts and noise variance. Experimental results on test images demonstrate that the Double-Density method achieves higher peak signal-to-noise ratios, especially at higher noise levels.
This document compares the k-means and grid density clustering algorithms. It summarizes that grid density clustering determines dense grids based on the densities of neighboring grids, and is able to handle different shaped clusters in multi-density environments. The grid density algorithm does not require distance computation and is not dependent on the number of clusters being known in advance like k-means. The document concludes that grid density clustering is better than k-means clustering as it can handle noise and outliers, find arbitrary shaped clusters, and has lower time complexity.
This document proposes a method for detecting, localizing, and extracting text from videos with complex backgrounds. It involves three main steps:
1. Text detection uses corner metric and Laplacian filtering techniques independently to detect text regions. Corner metric identifies regions with high curvature, while Laplacian filtering highlights intensity discontinuities. The results are combined through multiplication to reduce noise.
2. Text localization then determines the accurate boundaries of detected text strings.
3. Text binarization filters background pixels to extract text pixels for recognition. Thresholding techniques are used to convert localized text regions to binary images.
The method exploits different text properties to detect text using corner metric and Laplacian filtering. Combining the results improves
This document describes the design and implementation of a low power 16-bit arithmetic logic unit (ALU) using clock gating techniques. A variable block length carry skip adder is used in the arithmetic unit to reduce power consumption and improve performance. The ALU uses a clock gating circuit to selectively clock only the active arithmetic or logic unit, reducing dynamic power dissipation from unnecessary clock charging/discharging. The ALU was simulated in VHDL and synthesized for a Xilinx Spartan 3E FPGA, achieving a maximum frequency of 65.19MHz at 1.98mW power dissipation, demonstrating improved performance over a conventional ALU design.
This document describes using particle swarm optimization (PSO) and genetic algorithms (GA) to tune the parameters of a proportional-integral-derivative (PID) controller for an automatic voltage regulator (AVR) system. PSO and GA are used to minimize the objective function by adjusting the PID parameters to achieve optimal step response with minimal overshoot, settling time, and rise time. The results show that PSO provides high-quality solutions within a shorter calculation time than other stochastic methods.
This document discusses implementing trust negotiations in multisession transactions. It proposes a framework that supports voluntary and unexpected interruptions, allowing negotiating parties to complete negotiations despite temporary unavailability of resources. The Trust-x protocol addresses issues related to validity, temporary loss of data, and extended unavailability of one negotiator. It allows a peer to suspend an ongoing negotiation and resume it with another authenticated peer. Negotiation portions and intermediate states can be safely and privately passed among peers to guarantee stability for continued suspended negotiations. An ontology is also proposed to provide formal specification of concepts and relationships, which is essential in complex web service environments for sharing credential information needed to establish trust.
This document discusses and compares various nature-inspired optimization algorithms for resolving the mixed pixel problem in remote sensing imagery, including Biogeography-Based Optimization (BBO), Genetic Algorithm (GA), and Particle Swarm Optimization (PSO). It provides an overview of each algorithm, explaining key concepts like migration and mutation in BBO. The document aims to prove that BBO is the best algorithm for resolving the mixed pixel problem by comparing it to other evolutionary algorithms. It also includes figures illustrating concepts like the species model and habitat in BBO.
This document discusses principal component analysis (PCA) for face recognition. It begins with an introduction to face recognition and PCA. PCA works by calculating eigenvectors from a set of face images, which represent the principal components that account for the most variance in the image data. These eigenvectors are called "eigenfaces" and can be used to reconstruct the face images. The document then discusses how the system is implemented, including preparing a face database, normalizing the training images, calculating the eigenfaces/principal components, projecting the face images into this reduced space, and recognizing faces by calculating distances between projected test images and training images.
This document summarizes research on using wireless sensor networks to detect mobile targets. It discusses two optimization problems: 1) maximizing the exposure of the least exposed path within a sensor budget, and 2) minimizing sensor installation costs while ensuring all paths have exposure above a threshold. It proposes using tabu search heuristics to provide near-optimal solutions. The research also addresses extending the models to consider wireless connectivity, heterogeneous sensors, and intrusion detection using a game theory approach. Experimental results show the proposed mobile replica detection scheme can rapidly detect replicas with no false positives or negatives.
Threats to mobile devices are more prevalent and increasing in scope and complexity. Users of mobile devices desire to take full advantage of the features
available on those devices, but many of the features provide convenience and capability but sacrifice security. This best practices guide outlines steps the users can take to better protect personal devices and information.
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
“An Outlook of the Ongoing and Future Relationship between Blockchain Technologies and Process-aware Information Systems.” Invited talk at the joint workshop on Blockchain for Information Systems (BC4IS) and Blockchain for Trusted Data Sharing (B4TDS), co-located with with the 36th International Conference on Advanced Information Systems Engineering (CAiSE), 3 June 2024, Limassol, Cyprus.
Building Production Ready Search Pipelines with Spark and MilvusZilliz
Spark is the widely used ETL tool for processing, indexing and ingesting data to serving stack for search. Milvus is the production-ready open-source vector database. In this talk we will show how to use Spark to process unstructured data to extract vector representations, and push the vectors to Milvus vector database for search serving.
In the rapidly evolving landscape of technologies, XML continues to play a vital role in structuring, storing, and transporting data across diverse systems. The recent advancements in artificial intelligence (AI) present new methodologies for enhancing XML development workflows, introducing efficiency, automation, and intelligent capabilities. This presentation will outline the scope and perspective of utilizing AI in XML development. The potential benefits and the possible pitfalls will be highlighted, providing a balanced view of the subject.
We will explore the capabilities of AI in understanding XML markup languages and autonomously creating structured XML content. Additionally, we will examine the capacity of AI to enrich plain text with appropriate XML markup. Practical examples and methodological guidelines will be provided to elucidate how AI can be effectively prompted to interpret and generate accurate XML markup.
Further emphasis will be placed on the role of AI in developing XSLT, or schemas such as XSD and Schematron. We will address the techniques and strategies adopted to create prompts for generating code, explaining code, or refactoring the code, and the results achieved.
The discussion will extend to how AI can be used to transform XML content. In particular, the focus will be on the use of AI XPath extension functions in XSLT, Schematron, Schematron Quick Fixes, or for XML content refactoring.
The presentation aims to deliver a comprehensive overview of AI usage in XML development, providing attendees with the necessary knowledge to make informed decisions. Whether you’re at the early stages of adopting AI or considering integrating it in advanced XML development, this presentation will cover all levels of expertise.
By highlighting the potential advantages and challenges of integrating AI with XML development tools and languages, the presentation seeks to inspire thoughtful conversation around the future of XML development. We’ll not only delve into the technical aspects of AI-powered XML development but also discuss practical implications and possible future directions.
HCL Notes und Domino Lizenzkostenreduzierung in der Welt von DLAUpanagenda
Webinar Recording: https://www.panagenda.com/webinars/hcl-notes-und-domino-lizenzkostenreduzierung-in-der-welt-von-dlau/
DLAU und die Lizenzen nach dem CCB- und CCX-Modell sind für viele in der HCL-Community seit letztem Jahr ein heißes Thema. Als Notes- oder Domino-Kunde haben Sie vielleicht mit unerwartet hohen Benutzerzahlen und Lizenzgebühren zu kämpfen. Sie fragen sich vielleicht, wie diese neue Art der Lizenzierung funktioniert und welchen Nutzen sie Ihnen bringt. Vor allem wollen Sie sicherlich Ihr Budget einhalten und Kosten sparen, wo immer möglich. Das verstehen wir und wir möchten Ihnen dabei helfen!
Wir erklären Ihnen, wie Sie häufige Konfigurationsprobleme lösen können, die dazu führen können, dass mehr Benutzer gezählt werden als nötig, und wie Sie überflüssige oder ungenutzte Konten identifizieren und entfernen können, um Geld zu sparen. Es gibt auch einige Ansätze, die zu unnötigen Ausgaben führen können, z. B. wenn ein Personendokument anstelle eines Mail-Ins für geteilte Mailboxen verwendet wird. Wir zeigen Ihnen solche Fälle und deren Lösungen. Und natürlich erklären wir Ihnen das neue Lizenzmodell.
Nehmen Sie an diesem Webinar teil, bei dem HCL-Ambassador Marc Thomas und Gastredner Franz Walder Ihnen diese neue Welt näherbringen. Es vermittelt Ihnen die Tools und das Know-how, um den Überblick zu bewahren. Sie werden in der Lage sein, Ihre Kosten durch eine optimierte Domino-Konfiguration zu reduzieren und auch in Zukunft gering zu halten.
Diese Themen werden behandelt
- Reduzierung der Lizenzkosten durch Auffinden und Beheben von Fehlkonfigurationen und überflüssigen Konten
- Wie funktionieren CCB- und CCX-Lizenzen wirklich?
- Verstehen des DLAU-Tools und wie man es am besten nutzt
- Tipps für häufige Problembereiche, wie z. B. Team-Postfächer, Funktions-/Testbenutzer usw.
- Praxisbeispiele und Best Practices zum sofortigen Umsetzen
Pushing the limits of ePRTC: 100ns holdover for 100 daysAdtran
At WSTS 2024, Alon Stern explored the topic of parametric holdover and explained how recent research findings can be implemented in real-world PNT networks to achieve 100 nanoseconds of accuracy for up to 100 days.
Goodbye Windows 11: Make Way for Nitrux Linux 3.5.0!SOFTTECHHUB
As the digital landscape continually evolves, operating systems play a critical role in shaping user experiences and productivity. The launch of Nitrux Linux 3.5.0 marks a significant milestone, offering a robust alternative to traditional systems such as Windows 11. This article delves into the essence of Nitrux Linux 3.5.0, exploring its unique features, advantages, and how it stands as a compelling choice for both casual users and tech enthusiasts.
Best 20 SEO Techniques To Improve Website Visibility In SERPPixlogix Infotech
Boost your website's visibility with proven SEO techniques! Our latest blog dives into essential strategies to enhance your online presence, increase traffic, and rank higher on search engines. From keyword optimization to quality content creation, learn how to make your site stand out in the crowded digital landscape. Discover actionable tips and expert insights to elevate your SEO game.
UiPath Test Automation using UiPath Test Suite series, part 6DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 6. In this session, we will cover Test Automation with generative AI and Open AI.
UiPath Test Automation with generative AI and Open AI webinar offers an in-depth exploration of leveraging cutting-edge technologies for test automation within the UiPath platform. Attendees will delve into the integration of generative AI, a test automation solution, with Open AI advanced natural language processing capabilities.
Throughout the session, participants will discover how this synergy empowers testers to automate repetitive tasks, enhance testing accuracy, and expedite the software testing life cycle. Topics covered include the seamless integration process, practical use cases, and the benefits of harnessing AI-driven automation for UiPath testing initiatives. By attending this webinar, testers, and automation professionals can gain valuable insights into harnessing the power of AI to optimize their test automation workflows within the UiPath ecosystem, ultimately driving efficiency and quality in software development processes.
What will you get from this session?
1. Insights into integrating generative AI.
2. Understanding how this integration enhances test automation within the UiPath platform
3. Practical demonstrations
4. Exploration of real-world use cases illustrating the benefits of AI-driven test automation for UiPath
Topics covered:
What is generative AI
Test Automation with generative AI and Open AI.
UiPath integration with generative AI
Speaker:
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
GraphSummit Singapore | The Art of the Possible with Graph - Q2 2024Neo4j
Neha Bajwa, Vice President of Product Marketing, Neo4j
Join us as we explore breakthrough innovations enabled by interconnected data and AI. Discover firsthand how organizations use relationships in data to uncover contextual insights and solve our most pressing challenges – from optimizing supply chains, detecting fraud, and improving customer experiences to accelerating drug discoveries.
Communications Mining Series - Zero to Hero - Session 1DianaGray10
This session provides introduction to UiPath Communication Mining, importance and platform overview. You will acquire a good understand of the phases in Communication Mining as we go over the platform with you. Topics covered:
• Communication Mining Overview
• Why is it important?
• How can it help today’s business and the benefits
• Phases in Communication Mining
• Demo on Platform overview
• Q/A
Maruthi Prithivirajan, Head of ASEAN & IN Solution Architecture, Neo4j
Get an inside look at the latest Neo4j innovations that enable relationship-driven intelligence at scale. Learn more about the newest cloud integrations and product enhancements that make Neo4j an essential choice for developers building apps with interconnected data and generative AI.
Unlocking Productivity: Leveraging the Potential of Copilot in Microsoft 365, a presentation by Christoforos Vlachos, Senior Solutions Manager – Modern Workplace, Uni Systems