The document presents a modified fingerprint matching technique using fuzzy logic to match altered fingerprints. It aims to overcome limitations of existing techniques. Fingerprints are classified into three alteration categories: obliterated, distorted, and imitated. Spurious minutiae from altered regions are removed. Orientation field and minutiae distribution are analyzed to detect alterations. Fuzzy filtering is applied to unidentified regions to identify ridges, bifurcations, and minutiae. Experimental results show the technique improves matching performance over using all minutiae by removing spurious minutiae from altered regions. Ongoing research areas are discussed to further improve altered fingerprint matching.
A Challenge to Analyze and Detect Altered Human FingerprintsIOSR Journals
This document analyzes and proposes a method to detect altered human fingerprints. It discusses three main types of fingerprint alterations: obliteration, distortion, and imitation. It also outlines a system to 1) analyze altered fingerprints, 2) classify alterations, 3) demonstrate detection using a fingerprint database, and 4) develop an automatic detection technique using image processing and matching algorithms. The goal is to highlight the problem of altered fingerprints and propose an algorithm to identify them.
Study of Local Binary Pattern for Partial Fingerprint IdentificationIJMER
Fingerprints are usually used in recognition of a person's identity because of its uniqueness,
stability. Today also the matching of incomplete or partial fingerprints remains challenge. The current
technology is somewhat mature for matching ten prints, but matching of partial fingerprints still needs
a lot of improvement. Automatic fingerprint identification techniques have been successfully adapted to
both civilian and forensic applications. But this Fingerprint identification system suffers from the
problem of handling incomplete prints and discards any partial fingerprints obtained. Level 2 features
are very efficient if the quality of achievement decreases the number of level 2 features will not be
enough for establishing high accuracy in identification. In such cases pores (level 3 features) can be
used for partial fingerprint matching with the help of suitable technique local binary pattern features.
Local binary pattern feature is used to match the pore against with full fingerprints. The first step
involves extracting the pores from the partial image. These pores act as anchor points and sub window
(32*32) is formed surrounding the pores. Then rotation invariant LBP histograms are obtained from
the surrounding window. Finally chi-square formula is used to calculate the minimum distance between
two histograms to find best matching score
MDD Project Report By Dharmendra singh [Srm University] Ncr DelhiDharmendrasingh417
In this modern era, a huge revolution in technology is the introduction of biometric recognition system. One of the most useful biometric recognition system is fingerprint recognition system. The fingerprint recognition system is considered to most important biometric system in addition to other biometrics recognition systems
Latent fingerprint and vein matching using ridge feature identificationeSAT 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.
Biometric Fingerprint Recognintion based on Minutiae MatchingNabila mahjabin
The document summarizes a student's project on biometric fingerprint recognition based on minutiae matching. It includes an introduction to fingerprints and fingerprint recognition techniques. The project involves developing a complete fingerprint recognition system through minutiae extraction and matching. The system applies preprocessing techniques like image enhancement and binarization before extracting minutiae features from fingerprints. It then performs minutiae marking and false minutiae removal before matching fingerprints based on their minutiae patterns. The performance of the developed system is evaluated on a fingerprint database.
Review of three categories of fingerprint recognition 2prjpublications
This document reviews three categories of fingerprint recognition techniques: correlation-based, minutiae-based, and pattern-based. Minutiae-based matching is the most popular as minutiae points require less storage than images but it is more time-consuming than other methods. The correlation-based method matches entire fingerprint images and handles poor quality prints better but is computationally expensive. Pattern-based matching compares fingerprint swirl/loop patterns but requires consistent image alignment. Challenges include enhancing low-quality images and improving feature extraction, matching, and alignment algorithms.
Biometrics Authentication of Fingerprint with Using Fingerprint Reader and Mi...TELKOMNIKA JOURNAL
The idea of security is as old as humanity itself. Between oldest methods of security were
included simple mechanical locks whose authentication element was the key. At first, a universal–simple
type, later unique for each lock. A long time had mechanical locks been the sole option for protection
against unauthorized access. The boom of biometrics has come in the 20th century, and especially in
recent years, biometrics is much expanded in the various areas of our life. Opposite of traditional security
methods such as passwords, access cards, and hardware keys, it offers many benefits. The main benefits
are the uniqueness and the impossibility of their loss. The main benefits are the uniqueness and the
impossibility of their loss. Therefore we focussed in this paper on the the design of low cost biometric
fingerprint system and subsequent implementation of this system in praxtise. Our main goal was to create
a system that is capable of recognizing fingerprints from a user and then processing them. The main part
of this system is the microcontroller Arduino Yun with an external interface to the scan of the fingerprint
with a name Adafruit R305 (special reader). This microcontroller communicates with the external database,
which ensures the exchange of data between Arduino Yun and user application. This application was
created for (currently) most widespread mobile operating system-Android.
Seminar internasional Universitas Negeri SurakartaRizkyFaundra
1. The document presents an algorithm for iris segmentation and normalization based on the zigzag collarette area of the iris.
2. The algorithm uses Canny edge detection and circular Hough transform to localize the pupil and isolate the zigzag collarette area. It then applies Daugman's rubber sheet model to map the zigzag collarette onto polar coordinates for normalization.
3. An experiment of the algorithm achieved 98.88% accuracy at a threshold level of 0.3 for reducing edges near the pupil. The algorithm shows potential for use in iris recognition systems after further study of feature encoding and matching.
A Challenge to Analyze and Detect Altered Human FingerprintsIOSR Journals
This document analyzes and proposes a method to detect altered human fingerprints. It discusses three main types of fingerprint alterations: obliteration, distortion, and imitation. It also outlines a system to 1) analyze altered fingerprints, 2) classify alterations, 3) demonstrate detection using a fingerprint database, and 4) develop an automatic detection technique using image processing and matching algorithms. The goal is to highlight the problem of altered fingerprints and propose an algorithm to identify them.
Study of Local Binary Pattern for Partial Fingerprint IdentificationIJMER
Fingerprints are usually used in recognition of a person's identity because of its uniqueness,
stability. Today also the matching of incomplete or partial fingerprints remains challenge. The current
technology is somewhat mature for matching ten prints, but matching of partial fingerprints still needs
a lot of improvement. Automatic fingerprint identification techniques have been successfully adapted to
both civilian and forensic applications. But this Fingerprint identification system suffers from the
problem of handling incomplete prints and discards any partial fingerprints obtained. Level 2 features
are very efficient if the quality of achievement decreases the number of level 2 features will not be
enough for establishing high accuracy in identification. In such cases pores (level 3 features) can be
used for partial fingerprint matching with the help of suitable technique local binary pattern features.
Local binary pattern feature is used to match the pore against with full fingerprints. The first step
involves extracting the pores from the partial image. These pores act as anchor points and sub window
(32*32) is formed surrounding the pores. Then rotation invariant LBP histograms are obtained from
the surrounding window. Finally chi-square formula is used to calculate the minimum distance between
two histograms to find best matching score
MDD Project Report By Dharmendra singh [Srm University] Ncr DelhiDharmendrasingh417
In this modern era, a huge revolution in technology is the introduction of biometric recognition system. One of the most useful biometric recognition system is fingerprint recognition system. The fingerprint recognition system is considered to most important biometric system in addition to other biometrics recognition systems
Latent fingerprint and vein matching using ridge feature identificationeSAT 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.
Biometric Fingerprint Recognintion based on Minutiae MatchingNabila mahjabin
The document summarizes a student's project on biometric fingerprint recognition based on minutiae matching. It includes an introduction to fingerprints and fingerprint recognition techniques. The project involves developing a complete fingerprint recognition system through minutiae extraction and matching. The system applies preprocessing techniques like image enhancement and binarization before extracting minutiae features from fingerprints. It then performs minutiae marking and false minutiae removal before matching fingerprints based on their minutiae patterns. The performance of the developed system is evaluated on a fingerprint database.
Review of three categories of fingerprint recognition 2prjpublications
This document reviews three categories of fingerprint recognition techniques: correlation-based, minutiae-based, and pattern-based. Minutiae-based matching is the most popular as minutiae points require less storage than images but it is more time-consuming than other methods. The correlation-based method matches entire fingerprint images and handles poor quality prints better but is computationally expensive. Pattern-based matching compares fingerprint swirl/loop patterns but requires consistent image alignment. Challenges include enhancing low-quality images and improving feature extraction, matching, and alignment algorithms.
Biometrics Authentication of Fingerprint with Using Fingerprint Reader and Mi...TELKOMNIKA JOURNAL
The idea of security is as old as humanity itself. Between oldest methods of security were
included simple mechanical locks whose authentication element was the key. At first, a universal–simple
type, later unique for each lock. A long time had mechanical locks been the sole option for protection
against unauthorized access. The boom of biometrics has come in the 20th century, and especially in
recent years, biometrics is much expanded in the various areas of our life. Opposite of traditional security
methods such as passwords, access cards, and hardware keys, it offers many benefits. The main benefits
are the uniqueness and the impossibility of their loss. The main benefits are the uniqueness and the
impossibility of their loss. Therefore we focussed in this paper on the the design of low cost biometric
fingerprint system and subsequent implementation of this system in praxtise. Our main goal was to create
a system that is capable of recognizing fingerprints from a user and then processing them. The main part
of this system is the microcontroller Arduino Yun with an external interface to the scan of the fingerprint
with a name Adafruit R305 (special reader). This microcontroller communicates with the external database,
which ensures the exchange of data between Arduino Yun and user application. This application was
created for (currently) most widespread mobile operating system-Android.
Seminar internasional Universitas Negeri SurakartaRizkyFaundra
1. The document presents an algorithm for iris segmentation and normalization based on the zigzag collarette area of the iris.
2. The algorithm uses Canny edge detection and circular Hough transform to localize the pupil and isolate the zigzag collarette area. It then applies Daugman's rubber sheet model to map the zigzag collarette onto polar coordinates for normalization.
3. An experiment of the algorithm achieved 98.88% accuracy at a threshold level of 0.3 for reducing edges near the pupil. The algorithm shows potential for use in iris recognition systems after further study of feature encoding and matching.
This document provides an overview of multimodal biometric systems. It discusses various biometric modalities including fingerprint, palm print, iris, face, and voice. For each modality, it describes the basic methodology, including enrollment and recognition processes. It also reviews literature on implementations of unimodal and multimodal biometric systems using these physiological and behavioral traits. The document concludes that multimodal biometric systems that fuse information from multiple traits can provide more robust and accurate person identification compared to single-trait unimodal systems.
This document presents a new iris segmentation method for iris recognition systems. The proposed method uses Canny edge detection and Hough transform to locate the iris boundary after finding the pupil boundary using image gray levels. Experiments on the CASIA iris image database of 756 images show the method can accurately detect the iris boundary in 99.2% of images. This is an improvement over other existing segmentation techniques. The key steps of the proposed method are preprocessing, segmentation using Canny edge detection and Hough transform, normalization using the rubber sheet model, feature encoding with Gabor wavelets, and matching with Hamming distance.
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.
This document proposes fusing eye vein and finger vein biometrics for multimodal authentication. It extracts features from eye vein and finger vein images separately, then concatenates the feature vectors. Experimental results on public databases show this technique achieves more accurate identity verification than single biometrics, with lower false rejection and acceptance rates. The fused template provides better discrimination than individual features.
The paper explores iris recognition for personal identification and verification. In this paper a new iris recognition technique is proposed using (Scale Invariant Feature Transform) SIFT. Image-processing algorithms have been validated on noised real iris image database. The proposed innovative technique is computationally effective as well as reliable in terms of recognition rates.
Iris recognition is a method of biometric identification.
Biometric identification provides automatic recognition of an
individual based on the unique feature of physiological
characteristics or behavioral characteristic. Iris recognition is a
method of recognizing a person by analyzing the iris pattern.
This survey paper covers the different iris recognition techniques
and methods.
This document presents information on iris scanner technology from a presentation by Shams. It discusses what the iris is, why iris recognition is used, the history and development of iris recognition, how iris recognition systems work, advantages like the iris being unique and stable over time, and disadvantages like the small target size and it being obscured. The conclusion is that iris scanning is highly accurate and fast but still needs some development to become more widely used technology.
Software Implementation of Iris Recognition System using MATLABijtsrd
The software implementation of iris recognition system introduces in this paper. This system intends to apply for high security required areas. The demand on security is increasing greatly in these years and biometric recognition gradually becomes a hot field of research. Iris recognition is a branch of biometric recognition method. In thesis, Iris recognition system consists of localization of the iris region and generation of data set of iris images followed by iris pattern recognition. In thesis, a fast algorithm is proposed for the localization of the inner and outer boundaries of the iris region. Located iris is extracted from an eye image, and, after normalization and enhancement, it is represented by a data set. Using this data set a Neural Network NN is used for the classification of iris patterns. The adaptive learning strategy is applied for training of the NN. The implementation of the system is developed with MATLAB. The results of simulations illustrate the effectiveness of the neural system in personal identification. Finally, the accuracy of iris recognition system is tested and evaluated with different iris images. Mo Mo Myint Wai | Nyan Phyo Aung | Lwin Lwin Htay "Software Implementation of Iris Recognition System using MATLAB" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-3 | Issue-5 , August 2019, URL: https://www.ijtsrd.com/papers/ijtsrd25258.pdfPaper URL: https://www.ijtsrd.com/engineering/electronics-and-communication-engineering/25258/software-implementation-of-iris-recognition-system-using-matlab/mo-mo-myint-wai
This document summarizes iris scan technology. It discusses how iris recognition works by leveraging the unique patterns in the iris to provide accurate identification. The iris has over 400 identifying features and remains stable over time, making it a powerful biometric identifier. Iris scanning has applications in computer and device security, border control, and other areas requiring secure identification. While generally accurate, iris scanning does face some challenges related to acquisition of the iris image and potential non-cooperation of subjects.
Optimization of human finger knuckle print as a neoteric biometric identifierIRJET Journal
This document proposes developing a finger knuckle print-based biometric identification system. It involves preprocessing input images from video, extracting features using principal component analysis (PCA) and local binary patterns (LBP), and using a k-nearest neighbors (k-NN) classifier for matching. The system is tested on a database of finger knuckle print images from multiple individuals. Accuracy is calculated for both PCA+k-NN and LBP+k-NN approaches, with PCA+k-NN achieving higher accuracy of 93.33% compared to 86.67% for LBP+k-NN. Statistical features are also extracted from training and testing images of one individual to analyze feature consistency.
This document summarizes a research paper on latent fingerprint matching using descriptor-based Hough transform. It describes an approach that consists of three main steps: 1) aligning two sets of minutiae points using a descriptor-based Hough transform, 2) establishing correspondences between minutiae points, and 3) computing a similarity score. The goal is to develop an algorithm for automatically matching latent fingerprints to rolled fingerprints using only minutiae information. Experimental results on a public dataset show it outperforms a commercial fingerprint matcher.
Adaptive and Faster Approach to Fingerprint Minutiae Extraction and ValidationCSCJournals
Fingerprint has remained a very vital index in the field of security where series of Automatic Fingerprint Identification System (AFIS) have been developed for human identification. Many of these systems involve matching each of the features of a template image with each of the features in the feature sets in the reference database to determine the level of match between the template and the reference images. Matching is done on the basis of preset parameters such as feature type, location, orientation and so on. Obtaining the features from the template image and for building a reference database involves the implementation of a sound fingerprint feature detection and extraction algorithm. In this paper, the process of detecting and extracting false and valid features contained in a fingerprint image is discussed. Some of the existing fingerprint features extraction algorithms were firstly modified and the resulting algorithms were implemented. The implementation was carried out in an environment characterized by Window Vista Home Basic as platform and Matrix Laboratory (MatLab) as frontend engine. Fingerprints images of different qualities obtained from the manual (ink and paper) and electronic (fingerprint scanner) methods were used to test the adequacy of the resulting algorithms. The results obtained show that only valid and true minutiae points were extracted from the images.
The document discusses iris biometrics for identification. It describes the retina and iris, noting that the unique patterns of blood vessels and iris are highly distinctive even between identical twins. Iris recognition involves using cameras to capture high-resolution photos of the iris within a few feet. Software then locates the iris boundaries, normalizes it, and encodes the pattern to generate an iris code for identification purposes by comparing to stored templates. The iris remains stable over a lifetime but can be affected by some eye diseases. Compared to other biometrics, iris scanning is accurate, stable, fast, and scalable for identification.
This document discusses fingerprint-based person verification using MATLAB. It introduces fingerprint biometrics and processing images in the spatial and frequency domains. Fingerprints are a good biometric due to their universality, uniqueness, and permanence. The document describes classifying fingerprints based on patterns like loops and whorls. It also discusses representing fingerprints using minutiae points and applying biometrics to applications like access control and law enforcement.
1) The document describes a method for rapid visual recognition of personal identity based on analyzing the detailed texture of a person's iris.
2) An iris's texture is encoded into a compact "iris code" sequence of multi-scale 2-D Gabor wavelet coefficients. Statistical decision theory is used to generate identification decisions by comparing complete iris codes at 4000 comparisons per second.
3) Empirical tests show a theoretical "cross-over" error rate of one in 131,000 when adopting a decision criterion that equalizes false accept and reject rates. Given typical iris code agreement, decision confidence corresponds formally to a conditional false accept probability of about one in 10 billion.
Biometrics Iris Scanning: A Literature ReviewOlivia Moran
The interest in Biometrics from both governments and industry has lead to the emergence of multiple Biometric technologies all with their own strengths and flaws. One currently at the forefront of Biometrics is iris scanning.
The process involved in the identification and verification of people using iris scanning is examined in this paper. The advantages and disadvantages associated with the utilisation of such a technology are also explored. A number of legal and ethical issues are highlighted. Iris scanning is looked at in comparison to other forms of Biometric technologies. Future work in the area of Biometrics is also considered in light of current developments.
Study and development of Iris Segmentation and Normalization TechniqueSunil Kumar Chawla
The document is a thesis presentation on studying and developing iris segmentation and normalization techniques. It contains an introduction to biometrics and iris recognition. The document discusses literature on iris segmentation and normalization methods. It also covers topics like the anatomy and properties of the iris, existing iris recognition systems, and issues regarding biometrics. The goal is to develop an iris recognition system and evaluate its performance.
Reduction of False Acceptance Rate Using Cross Validation for Fingerprint Rec...IJTET Journal
Abstract— In the field of biometric modality fingerprint is considered to be one of the most widely used method for individual identity. The fingerprint authentication is used in most application for security purpose. In the biometric systems, the input images are binarized and feature is extraction. The Minutiae matching in fingerprint identification is done by identifying the minutiae point of interest and their relationship. The validation testing in the proposed system using the method of K- fold cross validation by using two , a training set and test set of images to find the appropriate image that matches the input image ,increase the accuracy of recognition by reducing the false acceptance rate of the system.
EFFECTIVENESS OF FEATURE DETECTION OPERATORS ON THE PERFORMANCE OF IRIS BIOME...IJNSA Journal
Iris Recognition is a highly efficient biometric identification system with great possibilities for future in the
security systems area.Its robustness and unobtrusiveness, as opposed tomost of the currently deployed
systems, make it a good candidate to replace most of thesecurity systems around. By making use of the
distinctiveness of iris patterns, iris recognition systems obtain a unique mapping for each person.
Identification of this person is possible by applying appropriate matching algorithm.In this paper,
Daugman’s Rubber Sheet model is employed for irisnormalization and unwrapping, descriptive statistical
analysis of different feature detection operators is performed, features extracted is encoded using Haar
wavelets and for classification hammingdistance as a matching algorithm is used. The system was tested on
the UBIRIS database. The edge detection algorithm, Canny, is found to be the best one to extract most of
the iris texture. The success rate of feature detection using canny is 81%, False Accept Rate is 9% and
False Reject Rate is 10%.
This document reviews energy efficient modulation and coding techniques for wireless sensor networks. It summarizes various modulation schemes (BPSK, QPSK, 16QAM, 64QAM) and error control codes (RS, BCH, convolutional) that have been studied. The document analyzes how these techniques can improve energy efficiency, bandwidth efficiency, and lifetime when applied to different channel conditions. Several research papers are summarized that evaluate the performance of these techniques in simulations and analysis. The conclusion is that optimal modulation and coding selection based on channel characteristics can improve energy consumption at sensor node transceivers.
The document discusses techniques for object recognition in images. It begins by outlining some of the challenges in object recognition, such as varying lighting, position, scale, and occlusion. It then describes several common object recognition techniques:
1. Template matching involves comparing images to stored templates but can be affected by changes in lighting, position, etc.
2. Color-based techniques use color histograms to match objects but require photometric invariance.
3. Local features represent objects with descriptors of local image patches but have limitations, while global features provide better recognition but are more complex to extract.
4. Shape-based methods match edge maps and contours between images and templates but require good segmentation.
The document
This document summarizes a research paper on matching altered fingerprints using fuzzy logic. It begins by classifying altered fingerprints into three categories: obliterated, distorted, and imitated. It then discusses challenges in matching altered fingerprints due to loss of minutiae from alterations. The proposed solution uses fuzzy logic to match altered fingerprints by replacing lost minutiae. It extracts minutiae from the valid, unaltered region and discards minutiae from altered regions that are unreliable. The method analyzes orientation fields and matches fingerprints while being robust to skin distortions from alterations.
This document provides an overview of multimodal biometric systems. It discusses various biometric modalities including fingerprint, palm print, iris, face, and voice. For each modality, it describes the basic methodology, including enrollment and recognition processes. It also reviews literature on implementations of unimodal and multimodal biometric systems using these physiological and behavioral traits. The document concludes that multimodal biometric systems that fuse information from multiple traits can provide more robust and accurate person identification compared to single-trait unimodal systems.
This document presents a new iris segmentation method for iris recognition systems. The proposed method uses Canny edge detection and Hough transform to locate the iris boundary after finding the pupil boundary using image gray levels. Experiments on the CASIA iris image database of 756 images show the method can accurately detect the iris boundary in 99.2% of images. This is an improvement over other existing segmentation techniques. The key steps of the proposed method are preprocessing, segmentation using Canny edge detection and Hough transform, normalization using the rubber sheet model, feature encoding with Gabor wavelets, and matching with Hamming distance.
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.
This document proposes fusing eye vein and finger vein biometrics for multimodal authentication. It extracts features from eye vein and finger vein images separately, then concatenates the feature vectors. Experimental results on public databases show this technique achieves more accurate identity verification than single biometrics, with lower false rejection and acceptance rates. The fused template provides better discrimination than individual features.
The paper explores iris recognition for personal identification and verification. In this paper a new iris recognition technique is proposed using (Scale Invariant Feature Transform) SIFT. Image-processing algorithms have been validated on noised real iris image database. The proposed innovative technique is computationally effective as well as reliable in terms of recognition rates.
Iris recognition is a method of biometric identification.
Biometric identification provides automatic recognition of an
individual based on the unique feature of physiological
characteristics or behavioral characteristic. Iris recognition is a
method of recognizing a person by analyzing the iris pattern.
This survey paper covers the different iris recognition techniques
and methods.
This document presents information on iris scanner technology from a presentation by Shams. It discusses what the iris is, why iris recognition is used, the history and development of iris recognition, how iris recognition systems work, advantages like the iris being unique and stable over time, and disadvantages like the small target size and it being obscured. The conclusion is that iris scanning is highly accurate and fast but still needs some development to become more widely used technology.
Software Implementation of Iris Recognition System using MATLABijtsrd
The software implementation of iris recognition system introduces in this paper. This system intends to apply for high security required areas. The demand on security is increasing greatly in these years and biometric recognition gradually becomes a hot field of research. Iris recognition is a branch of biometric recognition method. In thesis, Iris recognition system consists of localization of the iris region and generation of data set of iris images followed by iris pattern recognition. In thesis, a fast algorithm is proposed for the localization of the inner and outer boundaries of the iris region. Located iris is extracted from an eye image, and, after normalization and enhancement, it is represented by a data set. Using this data set a Neural Network NN is used for the classification of iris patterns. The adaptive learning strategy is applied for training of the NN. The implementation of the system is developed with MATLAB. The results of simulations illustrate the effectiveness of the neural system in personal identification. Finally, the accuracy of iris recognition system is tested and evaluated with different iris images. Mo Mo Myint Wai | Nyan Phyo Aung | Lwin Lwin Htay "Software Implementation of Iris Recognition System using MATLAB" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-3 | Issue-5 , August 2019, URL: https://www.ijtsrd.com/papers/ijtsrd25258.pdfPaper URL: https://www.ijtsrd.com/engineering/electronics-and-communication-engineering/25258/software-implementation-of-iris-recognition-system-using-matlab/mo-mo-myint-wai
This document summarizes iris scan technology. It discusses how iris recognition works by leveraging the unique patterns in the iris to provide accurate identification. The iris has over 400 identifying features and remains stable over time, making it a powerful biometric identifier. Iris scanning has applications in computer and device security, border control, and other areas requiring secure identification. While generally accurate, iris scanning does face some challenges related to acquisition of the iris image and potential non-cooperation of subjects.
Optimization of human finger knuckle print as a neoteric biometric identifierIRJET Journal
This document proposes developing a finger knuckle print-based biometric identification system. It involves preprocessing input images from video, extracting features using principal component analysis (PCA) and local binary patterns (LBP), and using a k-nearest neighbors (k-NN) classifier for matching. The system is tested on a database of finger knuckle print images from multiple individuals. Accuracy is calculated for both PCA+k-NN and LBP+k-NN approaches, with PCA+k-NN achieving higher accuracy of 93.33% compared to 86.67% for LBP+k-NN. Statistical features are also extracted from training and testing images of one individual to analyze feature consistency.
This document summarizes a research paper on latent fingerprint matching using descriptor-based Hough transform. It describes an approach that consists of three main steps: 1) aligning two sets of minutiae points using a descriptor-based Hough transform, 2) establishing correspondences between minutiae points, and 3) computing a similarity score. The goal is to develop an algorithm for automatically matching latent fingerprints to rolled fingerprints using only minutiae information. Experimental results on a public dataset show it outperforms a commercial fingerprint matcher.
Adaptive and Faster Approach to Fingerprint Minutiae Extraction and ValidationCSCJournals
Fingerprint has remained a very vital index in the field of security where series of Automatic Fingerprint Identification System (AFIS) have been developed for human identification. Many of these systems involve matching each of the features of a template image with each of the features in the feature sets in the reference database to determine the level of match between the template and the reference images. Matching is done on the basis of preset parameters such as feature type, location, orientation and so on. Obtaining the features from the template image and for building a reference database involves the implementation of a sound fingerprint feature detection and extraction algorithm. In this paper, the process of detecting and extracting false and valid features contained in a fingerprint image is discussed. Some of the existing fingerprint features extraction algorithms were firstly modified and the resulting algorithms were implemented. The implementation was carried out in an environment characterized by Window Vista Home Basic as platform and Matrix Laboratory (MatLab) as frontend engine. Fingerprints images of different qualities obtained from the manual (ink and paper) and electronic (fingerprint scanner) methods were used to test the adequacy of the resulting algorithms. The results obtained show that only valid and true minutiae points were extracted from the images.
The document discusses iris biometrics for identification. It describes the retina and iris, noting that the unique patterns of blood vessels and iris are highly distinctive even between identical twins. Iris recognition involves using cameras to capture high-resolution photos of the iris within a few feet. Software then locates the iris boundaries, normalizes it, and encodes the pattern to generate an iris code for identification purposes by comparing to stored templates. The iris remains stable over a lifetime but can be affected by some eye diseases. Compared to other biometrics, iris scanning is accurate, stable, fast, and scalable for identification.
This document discusses fingerprint-based person verification using MATLAB. It introduces fingerprint biometrics and processing images in the spatial and frequency domains. Fingerprints are a good biometric due to their universality, uniqueness, and permanence. The document describes classifying fingerprints based on patterns like loops and whorls. It also discusses representing fingerprints using minutiae points and applying biometrics to applications like access control and law enforcement.
1) The document describes a method for rapid visual recognition of personal identity based on analyzing the detailed texture of a person's iris.
2) An iris's texture is encoded into a compact "iris code" sequence of multi-scale 2-D Gabor wavelet coefficients. Statistical decision theory is used to generate identification decisions by comparing complete iris codes at 4000 comparisons per second.
3) Empirical tests show a theoretical "cross-over" error rate of one in 131,000 when adopting a decision criterion that equalizes false accept and reject rates. Given typical iris code agreement, decision confidence corresponds formally to a conditional false accept probability of about one in 10 billion.
Biometrics Iris Scanning: A Literature ReviewOlivia Moran
The interest in Biometrics from both governments and industry has lead to the emergence of multiple Biometric technologies all with their own strengths and flaws. One currently at the forefront of Biometrics is iris scanning.
The process involved in the identification and verification of people using iris scanning is examined in this paper. The advantages and disadvantages associated with the utilisation of such a technology are also explored. A number of legal and ethical issues are highlighted. Iris scanning is looked at in comparison to other forms of Biometric technologies. Future work in the area of Biometrics is also considered in light of current developments.
Study and development of Iris Segmentation and Normalization TechniqueSunil Kumar Chawla
The document is a thesis presentation on studying and developing iris segmentation and normalization techniques. It contains an introduction to biometrics and iris recognition. The document discusses literature on iris segmentation and normalization methods. It also covers topics like the anatomy and properties of the iris, existing iris recognition systems, and issues regarding biometrics. The goal is to develop an iris recognition system and evaluate its performance.
Reduction of False Acceptance Rate Using Cross Validation for Fingerprint Rec...IJTET Journal
Abstract— In the field of biometric modality fingerprint is considered to be one of the most widely used method for individual identity. The fingerprint authentication is used in most application for security purpose. In the biometric systems, the input images are binarized and feature is extraction. The Minutiae matching in fingerprint identification is done by identifying the minutiae point of interest and their relationship. The validation testing in the proposed system using the method of K- fold cross validation by using two , a training set and test set of images to find the appropriate image that matches the input image ,increase the accuracy of recognition by reducing the false acceptance rate of the system.
EFFECTIVENESS OF FEATURE DETECTION OPERATORS ON THE PERFORMANCE OF IRIS BIOME...IJNSA Journal
Iris Recognition is a highly efficient biometric identification system with great possibilities for future in the
security systems area.Its robustness and unobtrusiveness, as opposed tomost of the currently deployed
systems, make it a good candidate to replace most of thesecurity systems around. By making use of the
distinctiveness of iris patterns, iris recognition systems obtain a unique mapping for each person.
Identification of this person is possible by applying appropriate matching algorithm.In this paper,
Daugman’s Rubber Sheet model is employed for irisnormalization and unwrapping, descriptive statistical
analysis of different feature detection operators is performed, features extracted is encoded using Haar
wavelets and for classification hammingdistance as a matching algorithm is used. The system was tested on
the UBIRIS database. The edge detection algorithm, Canny, is found to be the best one to extract most of
the iris texture. The success rate of feature detection using canny is 81%, False Accept Rate is 9% and
False Reject Rate is 10%.
This document reviews energy efficient modulation and coding techniques for wireless sensor networks. It summarizes various modulation schemes (BPSK, QPSK, 16QAM, 64QAM) and error control codes (RS, BCH, convolutional) that have been studied. The document analyzes how these techniques can improve energy efficiency, bandwidth efficiency, and lifetime when applied to different channel conditions. Several research papers are summarized that evaluate the performance of these techniques in simulations and analysis. The conclusion is that optimal modulation and coding selection based on channel characteristics can improve energy consumption at sensor node transceivers.
The document discusses techniques for object recognition in images. It begins by outlining some of the challenges in object recognition, such as varying lighting, position, scale, and occlusion. It then describes several common object recognition techniques:
1. Template matching involves comparing images to stored templates but can be affected by changes in lighting, position, etc.
2. Color-based techniques use color histograms to match objects but require photometric invariance.
3. Local features represent objects with descriptors of local image patches but have limitations, while global features provide better recognition but are more complex to extract.
4. Shape-based methods match edge maps and contours between images and templates but require good segmentation.
The document
This document summarizes a research paper on matching altered fingerprints using fuzzy logic. It begins by classifying altered fingerprints into three categories: obliterated, distorted, and imitated. It then discusses challenges in matching altered fingerprints due to loss of minutiae from alterations. The proposed solution uses fuzzy logic to match altered fingerprints by replacing lost minutiae. It extracts minutiae from the valid, unaltered region and discards minutiae from altered regions that are unreliable. The method analyzes orientation fields and matches fingerprints while being robust to skin distortions from alterations.
This document discusses a new approach to providing secure data transmission that combines digital watermarking and image compression techniques. Digital watermarking involves embedding hidden information in multimedia content like images, audio or video. The proposed approach uses discrete cosine transform (DCT) based watermarking combined with an improved adaptive Huffman encoding image compression algorithm. This combined technique aims to enhance security for data transmission while reducing storage space requirements compared to other compression methods.
This document summarizes a research paper that proposes a new multiplier-accumulator (MAC) architecture for high-speed performance in digital signal processing applications. The proposed MAC architecture improves performance by combining the accumulator with the carry save adder tree, reducing the critical path. It also uses a modified Booth algorithm to reduce the number of partial products and a carry look-ahead adder to decrease the number of bits to the final adder. Experimental results show the proposed MAC architecture achieves a 35% reduction in delay compared to existing architectures.
This document discusses implementing trust-based route selection in mobile ad hoc networks. It proposes a system to store and update trust values for nodes based on their behavior. Different strategies are designed to evaluate routes based on the trust values of their constituent nodes. The performance of applying trust-based route selection to DSR, AODV and DYMO routing protocols is evaluated using the QualNet simulator in terms of metrics like throughput, packet delivery ratio and average jitter. The evaluation aims to improve routing performance and security in the presence of malicious nodes.
This document describes a combined approach to part-of-speech tagging using both features extraction and hidden Markov models. It analyzes a sample text to extract morphological features of words and assign part-of-speech tags. It then uses a hidden Markov model to determine the maximum probability of a tag based on previous tags for words that are ambiguous. The approach extracts features from unique words in different tags to build a features matrix to aid in part-of-speech tagging of unknown words based on their features.
This document describes the design and implementation of a voice activated, programmable, multipurpose robot. The robot uses a microcontroller and various integrated circuits to enable voice control and wireless control via dual-tone multi-frequency signaling. The document provides details on the circuit design and components, software design in C and Assembly languages, and concludes the robot demonstrates satisfactory performance for applications such as guiding visitors or patients.
This document proposes a video genre classification method using only audio features extracted from video clips. It uses Multivariate Adaptive Regression Splines (MARS) to build classification models for different genres based on low-level audio features like MFCCs, zero crossing rate, short-time energy, etc. Experiments on a dataset of news, cartoons, sports, dahmas and music clips achieved an overall classification rate of 91.83%, with certain features like MFCC3 and noise frame rate playing an important role in certain genre models.
Elastic distortion of fingerprints is one of the major causes for false non-match. While this problem affects all fingerprint recognition applications, it is especially dangerous in negative recognition applications, such as watchlist and deduplication applications
This document proposes enhancements to fingerprint recognition systems. It suggests selecting an optimal fingerprint feature vector for each authorized user by taking 10 fingerprints in different conditions and applying preprocessing, feature extraction, and a genetic algorithm to select a "master fingerprint" containing the most detailed global and local features. This master fingerprint would be stored in the database for matching. The proposal aims to improve systems by making the stored fingerprint more robust to noise and variations in finger placement. It may reduce false accept and reject rates compared to traditional single-fingerprint storage and matching.
Accurate Analysis on Hybrid DWT and SVD Based Digital Watermarking for Finger...IRJET Journal
This document proposes a new digital watermarking algorithm to improve the security of fingerprint data. The algorithm embeds a watermark into a fingerprint image using discrete wavelet transform (DWT) and singular value decomposition (SVD). It first converts the fingerprint image to the frequency domain using DWT. It then applies SVD to both the original fingerprint image and the watermark image. The singular values of the fingerprint image are modified with the singular values of the watermark image. This algorithm aims to increase the embedded information capacity and satisfy the transparency and robustness of the watermarking system.
Detection and rectification of distorted fingerprintsCloudTechnologies
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The document discusses a proposed system for detecting and rectifying distorted fingerprints. It begins with an abstract describing the problem of fingerprint distortion and the challenges it poses for fingerprint recognition systems. It then provides details on the existing approaches which have limited capabilities in detecting altered fingerprints. The proposed system is evaluated at the finger and subject level. It detects altered fingerprints using features extracted from the orientation field and minutiae distribution. Promising results were obtained on three databases. The system aims to address security issues around criminals distorting fingerprints to evade identification.
Iaetsd latent fingerprint recognition and matchingIaetsd Iaetsd
The document discusses latent fingerprint recognition and matching using statistical texture analysis. It proposes extracting three statistical features from fingerprints - entropy coefficient from intensity histogram, correlation coefficient using Wiener filter, and wavelet energy coefficient from 5-level wavelet decomposition. These features are used to represent fingerprints mathematically and provide efficient fingerprint recognition. Existing fingerprint recognition methods are also discussed, including those based on minutiae matching and dealing with nonlinear distortions. However, these do not fully address the problem. The proposed statistical analysis approach can provide more accurate recognition results.
Enhanced Latent Fingerprint Segmentation through Dictionary Based ApproachEditor IJMTER
The accuracy of latent finger print matching compared to roll and plain finger print
matching is significantly lower due to background noise, poor ridge quality and overlapping
structured noise in latent images. In this paper the proposed algorithm is dictionary-based approach
for automatic segmentation and enhancement towards the goal of achieving “lights out” latent
identifications system. Total variation decomposition model with L1 fidelity regularization in latent
finger print image remove background noise. A coarse to fine strategy is used to improve robustness
and accuracy. It improves the computational efficiency of the algorithm.
Biometric system works on behavioral and physiological biometric parameters to spot a person. Every fingerprint contains distinctive options and its recognizing system primarily works on native ridge feature local ridge endings, minutiae, core point, delta, etc. However, fingerprint pictures have poor quality thanks to variations in skin and impression conditions. In personal identification, fingerprint recognition is taken into account the foremost outstanding and reliable technique for matching with keep fingerprints within the information. Minutiae extraction is additional essential step in fingerprint matching. This paper provides plan regarding numerous feature extraction and matching algorithms for fingerprint recognition systems and to seek out that technique is additional reliable and secure.
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.
Latent fingerprints lifted from crime scenes often contain overlapping prints, which are
difficult to separate and match by state-of-the-art fingerprint matchers. The methods that have been
proposed to separate overlapping fingerprints and successful matching previously suffer from limited
accuracy of the estimated orientation field. In this paper, the robustness of overlapping fingerprints
separation is increased, particularly for low quality images. This algorithm reconstructs the
orientation fields of component prints by modeling fingerprint orientation fields. To facilitate this,
orientation cues of component fingerprints are utilized, which are manually marked by fingerprint
examiners. The effectiveness of this model has been evaluated.
This document summarizes a research paper that presents a new algorithm for separating overlapping latent fingerprints. The algorithm first models the orientation fields of each fingerprint component using singular points and a small number of manually marked orientation cues. It then reconstructs the orientation fields of the components by predicting unknown orientation values based on the model. This approach improves over prior methods that estimated a mixed orientation field from the overlapping image. By leveraging a fingerprint orientation field model and manual cues, the new algorithm can more accurately separate overlapping fingerprints, especially those of poor quality, which is important for forensic applications.
A Novel Approach to Fingerprint Identification Using Gabor Filter-BankIDES Editor
Fingerprint Identification is a widely used Biometric
Identification mechanism. Up till now different techniques
have been proposed for having satisfactory Fingerprint
Identification. The widely used minutiae-based representation
did not utilize a significant component of the rich
discriminatory information available in the fingerprints. Local
ridge structures could not be completely characterized by
minutiae. The proposed filter-based algorithm uses a bank of
Gabor filters to capture both local and global details in a
fingerprint as a compact fixed length Finger Code. The
Fingerprint Identification is based on the Euclidean distance
between the two corresponding Finger Codes and hence is
extremely fast and accurate than the minutiae based one.
Accuracy of the system is 98.22%.
Multiple features based fingerprint identification systemeSAT Journals
Abstract Security has become major issue now a day. In order to prevent unauthorized access of confidential data there is a need for accurate and reliable personal identification system. So, biometric based identification system is one of the best solutions. Fingerprint based system is one of oldest biometric identification systems. It is used in many commercial and security applications. Even with advent of technology in fingerprint identification system, the accurate extraction and matching of features from a fingerprint image is a challenging task. The task is much more challenging when fingerprint is affected by non-linear deformations such as rotation and translation. In this paper, fingerprint identification system using improved feature vector based algorithm is presented. In the algorithm Gabor filter is implemented to enhance the fingerprint image. The salient features minutiae (ridge endings) and reference point are extracted from the image. The Euclidian distances between reference point and each minutiae point are calculated and are arranged in ascending order. These are stored in database as feature vectors. The fingerprint matching is done based on the similarity rate between the feature vector of input fingerprint and the feature vectors stored in the database. Algorithms are implemented using Visual Studio 2010 in C++ language using Open CV libraries and tested on the fingerprint database created in the laboratory. Key Words: Fingerprint, Minutiae, Reference point, Euclidian distance, Similarity rate, Identification
IRJET- Sixth Sense Hand-Mouse Interface using Gestures & Randomized KeyIRJET Journal
The document proposes a sixth sense ATM machine that enables contactless transactions using hand gestures recognized by cameras rather than physical interfaces, eliminating the spread of bacteria while also incorporating sensors to prevent theft and monitor users to increase security. Current ATM systems are susceptible to bacterial spread through physical interfaces and card/PIN skimming, while proposed solutions in previous research had limitations, so the sixth sense ATM aims to address both issues simultaneously through a non-touch gesture-based interface and integrated alarm sensors.
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.
Detection and rectification of distorted fingerprintJayakrishnan U
This document discusses challenges in fingerprint recognition related to low quality fingerprints and distortions. It summarizes approaches to detect distorted fingerprints and rectify them for fingerprint matching. The key approaches discussed are:
1. Detecting distortions by analyzing registered ridge orientation and period maps of fingerprints as feature vectors.
2. Rectifying distortions by searching a reference database of distorted fingerprints to find the nearest neighbor and corresponding distortion field to inverse transform the input fingerprint.
3. Evaluating these approaches on benchmark datasets shows improved detection of distorted fingerprints and higher matching accuracy after rectification compared to previous methods.
This document summarizes a survey on enhancing and developing countermeasures for fingerprint authentication systems. It discusses common spoofing attacks and errors in fingerprint systems. It also reviews related work on fingerprint patterns and features. Methods to enhance fingerprint matching include thinning ridges, segmenting regions of interest, and extracting ridge contours. The document also discusses hardware-based and software-based liveness detection techniques to prevent spoofing, such as analyzing perspiration and texture. The goal of the survey is to improve fingerprint authentication performance and security by addressing vulnerabilities.
This document presents a method for extracting high resolution features from internal fingerprints imaged using optical coherence tomography (OCT). The method involves fitting a curve to remove curvature from cross-sectional OCT scans of the fingertip papillary layer. Straightened cross-sections are concatenated to form a 2D internal fingerprint image, which is enhanced using filters. Minutiae features are then extracted from the image at high resolution (1300 dpi) and evaluated by matching to manually extracted features, achieving similarity scores above 0.6. The method provides a way to extract discriminating fingerprint features from internal fingerprint images without external skin limitations, but performance is still affected by fingertip motion during imaging.
The document summarizes biometric security and fingerprint recognition technology. It defines biometrics as using physical or behavioral traits like fingerprints, iris, face, voice or handwriting to identify individuals. Fingerprints are widely used for authentication and various fingerprint recognition techniques are described, including minutiae-based matching of ridge endings and bifurcations. Applications of fingerprint biometrics include security systems, criminal identification, and border control. Emerging areas include 3D and multi-view fingerprint capture to overcome limitations of contact sensors.
This document proposes an algorithm to detect fingerprint distortion from a single image. The algorithm analyzes ridge period and orientation information in specific regions of the fingerprint. It computes the standard deviation of ridge period in the top region of the fingerprint to detect inconsistencies caused by distortion. It also analyzes the mean curvatures of the ridge orientation field in the top region, as distorted fingerprints may have ridges with smaller or even convex curvature compared to normal fingerprints. Promising results were obtained when testing the algorithm on a public fingerprint database containing distorted fingerprints. The algorithm can help address security issues caused by criminals intentionally distorting their fingerprints to evade identification.
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.
inQuba Webinar Mastering Customer Journey Management with Dr Graham HillLizaNolte
HERE IS YOUR WEBINAR CONTENT! 'Mastering Customer Journey Management with Dr. Graham Hill'. We hope you find the webinar recording both insightful and enjoyable.
In this webinar, we explored essential aspects of Customer Journey Management and personalization. Here’s a summary of the key insights and topics discussed:
Key Takeaways:
Understanding the Customer Journey: Dr. Hill emphasized the importance of mapping and understanding the complete customer journey to identify touchpoints and opportunities for improvement.
Personalization Strategies: We discussed how to leverage data and insights to create personalized experiences that resonate with customers.
Technology Integration: Insights were shared on how inQuba’s advanced technology can streamline customer interactions and drive operational efficiency.
Must Know Postgres Extension for DBA and Developer during MigrationMydbops
Mydbops Opensource Database Meetup 16
Topic: Must-Know PostgreSQL Extensions for Developers and DBAs During Migration
Speaker: Deepak Mahto, Founder of DataCloudGaze Consulting
Date & Time: 8th June | 10 AM - 1 PM IST
Venue: Bangalore International Centre, Bangalore
Abstract: Discover how PostgreSQL extensions can be your secret weapon! This talk explores how key extensions enhance database capabilities and streamline the migration process for users moving from other relational databases like Oracle.
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ScyllaDB is making a major architecture shift. We’re moving from vNode replication to tablets – fragments of tables that are distributed independently, enabling dynamic data distribution and extreme elasticity. In this keynote, ScyllaDB co-founder and CTO Avi Kivity explains the reason for this shift, provides a look at the implementation and roadmap, and shares how this shift benefits ScyllaDB users.
High performance Serverless Java on AWS- GoTo Amsterdam 2024Vadym Kazulkin
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JavaLand 2024: Application Development Green Masterplan
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Volume 2, No 5, May 2013
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Modified Dactylogram Sifting
Geethu V S1
, V.Selvakumar2
1
Dept.of ECE, Sri Lakshmi Aammal Engineering College, Chennai.
2
Asst Prof Dept.of ECE, Lakshmi Aammal Engineering College, Chennai.
Abstract— Fingerprint recognition has been with success
utilized by enforcement agencies to spot suspects and
victims for nearly a hundred years. Recent advances in
automated fingerprint identification technology, in
addition the growing would like for reliable person
identification, have resulted in an increased use of
fingerprints in both government and civilian applications
such as border control, employment background checks,
and secure facility access. Fingerprint obfuscation refers
to the deliberate alteration of the fingerprint pattern by an
individual for the purpose of masking his identity.
Classify altered fingerprints into three classes based on
the changes in ridge pattern due to alteration as
obliterated, distorted and imitated. The projected
algorithmic rule supported the trivialities based on the
minutiae extracted satisfies the essential requirements and
determine the alteration type automatically to reconstruct
altered fingerprints. In order to conquer the drawbacks of
existing techniques, we proposed an efficient and robust
fingerprint matching technique via fuzzy based method.
For some types of altered fingerprints where the ridge
patterns are damaged locally or the ridge structure is still
present on the finger but possibly at a different location,
reconstruction is indeed possible by the proposed method.
Further it is shown that authentication is retained even
though fingerprint identity has altered.
Keywords:Fingerprints,Alteration,Obfuscation,Minutiae
extraction,Fuzzy based method
I. INTRODUCTION
Fingerprint matching has been successfully used by law
enforcement for more than a century. The technology is
now finding many other applications such as identity
management and access control. The automated fingerprint
recognition system and identify key challenges and research
opportunities in the field. Fingerprint alteration refers to
changes made in a person‟s finger ridge structure by means
of abrading, cutting, or performing plastic surgery on the
fingertips. Finger-print alteration is a serious attack on
Automated Finger-print Identification Systems (AFIS)
since it can reduce the similarity between fingerprint
impressions from the same finger due to the loss of genuine
minutiae, increase in spu-rious minutiae and distortion in
spatial distribution of the minutiae. The widespread
deployment of AFIS gives incentive to some individuals,
e.g., criminals and illegal aliens, to evade fingerprint
identification by altering their fingerprints. The objective of
fingerprint alteration, also called fingerprint obfuscation, is
to conceal one‟s identity by abrading, cutting, burning
fingers or performing plastic surgery on fingertips [1]. If a
person has a prior criminal record, he hopes that his altered
fingerprints will not be successfully matched to his
reference fingerprints stored in the law enforcement
databases.
We classify altered fingerprints into three
categories based on the changes in ridge pattern due to
alteration. This categorization will assist us in following
manner: 1) Getting a better understanding of the nature of
alterations that can be encountered, 2) detecting altered
fingerprints by modeling well-defined subcategories, and 3)
developing methods for altered fingerprint restoration. The
US Department of Homeland Security‟s US-VISIT
program (www.dhs.gov/usvisit) provides visa-issuing posts
and ports of entry with fingerprint recognition technology
that enables the federal government to establish and verify
the identity of those visiting the US. This large-scale
automated fingerprint recognition system has processed
more than 100 million visitors to the US since 2004.
In order to extract precise minutiae information,
an input fingerprint image generally needs to be enhanced
by convolving with certain types of orientation-selective
filters, such as Gabor or steerable filters, along the ridge
flow orientation at each pixel/block location [2, 3].The
minutiae considered involve ridge ending and bifurcation.
Figure-1a: Ridge ending Figure-1b:
Bifurcation
Altered fingerprint matching is a challenging
problem due to the following reasons: (i) friction ridge
structure can be severely damaged by abrading, cutting,
burning, or applying strong chemicals on fingertips,
resulting in a number of unreliable minutiae (ii) even if the
ridge
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Figure-2: Photograph of altered fingerprint a) Transplanted friction ridge from skin sole b)Fingers that have been
bitten c)Fingers burnt by acid d)Stitched fingers
structure is well-defined in local regions, minutiae
distribution can be highly unusual during the procedure of
switching skin patches in cases of „Z‟-cut prints (Fig. 3a);
and (iii) minutiae in well-defined ridge area may not belong
to the fingerprint of interest if a portion of skin on the
fingertip was transplanted from other parts of the body
.Figure-2 shows the different types of alteration in
fingerprint. Matching phase can be divided into two parts:
(i) altered fingerprint restoration and (ii) altered fingerprint
matching. The matching of altered fingerprint with the
unaltered fingerprint stored in the database is the current
work. Matching done using fuzzy logic by replacing the
lost minutiae with the existing minutiae. Further it is shown
that authentication is retained
II. RELATED WORK
Algorithms that provide better detection
compared to NFIQ algorithm that can detect only up to 20
percent of altered fingerprint are defined. Here only two
types of altered fingerprint is detected, because the image
quality of obliterated fingerprint is either so good that they
can be successfully matched to the mated fingerprint by
automatic matchers or so poor that they can be easily
detected by fingerprint quality control software and
imitated fingerprints may look very natural and they are no
images of this type currently available in the public domain
to undertake such a study. Orientation field estimation and
singular point detection is done to detect alteration. Due to
the variation of singular points in terms of their number and
location, the orientation field of natural fingerprints varies
across individuals. Another approach for altered fingerprint
detection is: minutiae–based and correlation-based. The
former has several advantages over the latter such as lower
time complexity, better space complexity, less requirement
of hardware etc. The uniqueness of a fingerprint is due to
unique pattern shown by the locations of the minutiae
points – irregularities of a fingerprint – ridge endings, and
bifurcations.
Altered fingerprint types, „Z‟-cut cases are of
special interest since the original ridge structure of the
finger is still retained in the finger, but in different
positions. Once the „Z‟-cut prints are detected[4], the ridge
structure in the triangular patches can be restored by
reversing the transposing procedure. The restored „Z‟-cut
fingerprint and all other altered fingerprints are submitted
to a special matcher which is robust to a large amount of
skin distortion and utilizes local minutiae information.
III. PROPOSED SOLUTION
Motivated by the existing system‟s problem we
present a new matching technique for altered fingerprint
using fuzzy logic which is capable of matching all possible
altered fingerprint patterns. Performance is higher
compared to the existing systems.
Database
A large database of altered fingerprints is
obtainable to us from a law enforcement agency. It contains
4,433 altered fingerprints from 535 tenprint cards of 270
subjects. Among these altered images, if multiple pre-
altered impressions of a finger exist, the simplest quality
fingerprint image assessed by NIST Fingerprint Image
Quality (NFIQ) software [5] is selected as a reference
fingerprint.
Spurious Minutiae in Altered Region
Minutiae in the altered region are most likely
unreliable since, for instance, scars generate abrupt ridge
endings and mutilation forms unusual ridge pattern. In
transplanted cases, the ridge structure in the altered region
does not belong to the finger of interest. Valid fingerprint
region in the altered fingerprint is defined as the unaltered
region where genuine friction ridge structure of the finger
appears. To establish the valid fingerprint region, region of
interest (ROI) of a fingerprint is obtained by measuring
dynamic range in local regions, and altered regions also are
manually marked. ROI is defined as the local image blocks
with dynamic range in gray-scale intensity over 20 after the
highest and the lowest 10% gray values in a block are
discarded. This is followed by morphological operators to
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fill holes and remove isolated small regions. With the
altered region that is currently marked manually, spurious
minutiae in invalid fingerprint region (i.e., either in the
altered region or outside ROI) are discarded. The number of
valid minutiae can vary a lot according to the area of valid
fingerprint region.
Restoration and Matching of Altered Fingerprint
Figure 4: Flow Chart for Matching of Altered Fingerprint
Analysis of Orientation Field
Orientation field describes the ridge flow of
fingerprints. Good quality fingerprints have a smooth
orientation field except near the singular points (e.g., core
and delta).Based on this fact, many orientation field models
have been developed by combining the global orientation
field model for the continuous flow field of the fingerprint
with the local orientation field model around the singular
points. The global orientation field model represents either
arch-type fingerprints, which do not have any singularity,
or the overall ridge orientation field except singularity in
fingerprints. If the global orientation field model alone is
used for orientation field approximation, the difference
between the observed orientation field and the model will
ideally be nonzero only around the singular points. On the
other hand, for obfuscated fingerprints, the model fitting
error is observed in the altered region as well. Thus, we use
the difference between the observed orientation field
extracted from the fingerprint image and the orientation
field approximated by the model as a feature vector for
classifying a fingerprint as natural fingerprint or altered
one.
Analysis of Minutiae Distribution
Based on the minutiae extracted from the
Altered-fingerprint by the minutiae extractor in, minutiae
density map is constructed by using the Parzen window
method with uniform kernel function. Kernel density
estimation is a non parametric way to estimate the
probability density function. Let Sm be the set of minutiae
of the fingerprint,
Sm = {x|x=(x,y) is the position of minutiae}
Then, the minutiae density map from Sm is computed as
follows:
The initial minutiae density map, Md(x), is
obtained by
Md(x) = ∑ Kr(x-x0)
Kr(x-x0) uniform kernel function centered at x0 with
radius r.
Low-pass filtering Md(x,y) is smoothed by a
Gaussian filter of size 30 X 30 pixels with a standard
deviation of 10 pixels. Normalization. Md(x,y) is
transformed to lie in the interval [0 1] by
Md(x,y) = { Md(x,y)/T, if Md(x,y) ≤ T
1 , otherwise
Where T is a predetermined threshold.
The minutiae density maps of altered fingerprints
are detected. In the natural fingerprint, minutiae are well
spread and distributed almost uniformly. In the altered
fingerprints, on the other hand, the distributions of minutiae
are quite different: 1) Many spurious minutiae are extracted
along scars and in the obliterated region due to ridge
discontinuity, and 2) an excessive number of minutiae
appear when a new ridge-like pattern is formed after
alteration. The examples demonstrate that minutiae
distribution can be useful for detecting altered fingerprints.
Restoration and Matching
Finger Print Matching Algorithm
1. Divide an input image into non overlapping
blocks with size x*y
2. Compute the gradients ∂x(i, j) and ∂y(i, j) at each
pixel (i, j) which is the centre of the block. The
gradient operator can be chosen according to the
computational complexity.
3. For each unidentified region apply fuzzy
filtering(i.e. copying neighbouring pixels)
a. Identify ridges, bifurcated area and
minutia by applying local orientation
b. Local Orientation algorithm calculates
the threshold value of the pixel region.
Here, the θ (i, j) is the least square estimate of the
local ridge orientation of the block centered at
pixel (i,j).
c. Apply Fine turning Operation as shown
below
MINUTIAE
EXTRACTION
MINUTIAE
DENSITY MAP
FEATURE LEVEL
FUSION
MATCH STAGE (FCM)
PRE ALTERED
FINGERPRINT
ALTERED
FINGERPRINT
ORIENTATION
FIELD
ESTIMATION
ORIENTATION
FIELD
DISCONTINUITY
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d. Apply fuzzy on following clusters
4. Check the image with existing database image
IV. IMPLEMENTATION AND EXPERIMENTAL
RESULTS
Matching performance of altered fingerprints is
evaluated by the Cumulative Match Characteristic (CMC)
curves. We view altered fingerprint matching in the same
spirit as latent fingerprint matching in the sense that these
are high profile cases where a forensic examiner needs to
examine top N retrieved candidates from the background
database.
As a fingerprint matcher, Neurotechnology
VeriFinger SDK 6.3 is used to extract minutiae and match
the minutiae templates. The altered fingerprint database
consists of 1,332 pre/post-altered fingerprint pairs. Three
minutiae sets are evaluated: (i) all the minutiae extracted
from the altered fingerprints, (ii) a subset of minutiae from
the altered fingerprints by removing spurious minutiae in
invalid fingerprint region, and (iii) a subset of minutiae
from the restored fingerprint image by removing spurious
minutiae in invalid fingerprint region. Note that all the
minutiae in altered fingerprints are automatically extracted
by the matcher, and then spurious minutiae in invalid
region are masked out.
Fingerprint alteration is not always successful in lowering
the genuine match scores. Furthermore, the severity of the
alteration does not predict degradation in matching
performance. The fingerprint alteration appears to be severe
due to the skin transplantation over a large area. However,
it can be successfully matched to its pre-altered mate; the
match score with its true mate is sufficiently high to be
correctly identified at the top rank. Removal of spurious
minutiae in the altered region can improve the matching
performance. In most of altered fingerprint matching, it is
observed that minutiae pairing results are globally
inconsistent due to a number of spurious minutiae from
scars, mutilated region or background. By removing
spurious minutiae, the matcher is able to find more
consistent mates in minutiae pairings, which results in
higher genuine match score.
Figure 5: Match Score of pre /post alteration fingerprint
pairs according to type and genuine and impostor pairs
V.CONCLUSIONS AND FURTHER RESEARCH
Reconstruction of altered fingerprints is done. For
some types of altered fingerprints where the ridge patterns
are damaged locally or the ridge structure is still present on
the finger but possibly at a different location, reconstruction
is indeed possible. Match altered fingerprints to their
unaltered mates. A matcher specialized for altered
fingerprints can be developed to link them to unaltered
mates in the database utilizing whatever information is
available in the altered fingerprints. Previous work on this
topic [10,1] addressed the automatic detection of altered
fingerprints based on the abnormality in orientation field
and minutiae distribution.
Ongoing research on matching altered fingerprints is
addressing the following topics:
• Localize the altered region automatically to improve the
matching performance by removing spurious minutiae in
the altered region as well as classify„Z‟-cut cases which are
of special interest due to the possibility of restoration;
• Develop a new fingerprint matching algorithm specialized
to altered fingerprint matching which is robust to skin
distortion and that maximally uses local ridge structure in
valid fingerprint region
• Use multibiometrics [6] to combat the growing threat of
individuals evading AFIS. Federal agencies in the United
States have adopted or are planning to adopt
multibiometrics in their identity management systems (the
FBI‟s NGI [7] and DoD‟s ABIS [8]). However, other
biometric traits can also be altered successfully. It has been
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reported that plastic surgery can significantly degrade the
performance of face recognition systems [9] and that
cataract surgery can reduce the accuracy of iris recognition
systems [10]. To effectively deal with the problem of
evading identification by altering biometric traits, a
systematic study of possible alteration approaches for each
major biometric trait is needed.
ACKNOWLEDGEMENT
We wish to express our sincere thanks to all the staff
member of E.C.E Department, Sri Lakshmi Aammal
Engineering College for their help and cooperation.
VI . REFERENCES
[1] S. Yoon, J. Feng , and A. K. Jain. Altered fingerprints:
Analysis and detection. IEEE Trans. Pattern Analysis and
Machine Intelligence , 2012.
[2] L. Hong, Y. Wan, and A. Jain, “Fingerprint image
enhancement: Algorithm and performance evalution,” IEEE
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no. 8, pp. 777–789, 1998.
[3] R. Bolle S. Chikkerur, S. Pankanti and V. Govindaraju,
“Minutiae verification in fingerprint images using steerable
wedge filters,” in Indian Conf. on Computer Vision,
Graphics & Image Processing,2004.
[4] On Matching Altered Fingerprints Soweon Yoon, Qijun
Zhao, and Anil K. Jain Department of Computer Science
and Engineering Michigan State University East Lansing,
MI, U.S.A. {yoonsowo,qjzhao,jain}@cse.msu.edu
[5] E. Tabassi, C. Wilson, and C. Watson. Fingerprint
Imagequality.NISTIR7151,August2004.http://fingerprint.ni
st.gov/NFIS/ir_7151.pdf.
[6] The FBI‟s Next Generation Identification (NGI),
http://www.fbi. gov/hq/cjisd/ngi.htm, 2011.
[7]DoD Biometrics Task Force,
http://www.biometrics.dod.mil/, 2011.
[8] R. Singh, M. Vatsa, H.S. Bhatt, S. Bharadwaj, A.
Noore, and S.S. Nooreyezdan, “Plastic Surgery: A New
Dimension to Face Recognition,” IEEE Trans. Information
Forensics and Security, vol. 5, no. 3, pp. 441-448, Sept.
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[9] R. Roizenblatt, P. Schor, F. Dante, J. Roizenblatt, and
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[10] J. Feng, A. K. Jain, and A. Ross. Detecting Altered
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