A hybrid method for iris segmentation

Advance development in security technology has caused many major corporations and governments to start employing modern techniques in identifying the identity of the individuals. Among the common biometric identification methods are facial recognition, fingerprint recognition, speaker verification a...

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Main Author:	Mohammed Mukred, Muaadh Shaif
Format:	Thesis
Language:	English
Published:	2010
Subjects:	QA75 Electronic computers Computer science
Online Access:	http://eprints.utm.my/id/eprint/16448/1/MuadhShaifMohammedMFSKSM2010.pdf
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id	my-utm-ep.16448
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spelling	my-utm-ep.164482017-09-13T03:30:18Z A hybrid method for iris segmentation 2010 Mohammed Mukred, Muaadh Shaif QA75 Electronic computers. Computer science Advance development in security technology has caused many major corporations and governments to start employing modern techniques in identifying the identity of the individuals. Among the common biometric identification methods are facial recognition, fingerprint recognition, speaker verification and so on, present a new solution for applications that require a high degree of security. Among these biometric methods, iris recognition becomes an important topic in pattern recognition, and it depends on the iris which is located in a place that still stable through human life. Furthermore, the probability to find two identical iris's approaching to zero value is quite easy. The identification system consists of several stages, and segmentation is the most crucial step. The current segmentation methods still have limitation in localizing the iris due to circular shape consideration of the pupil. Therefore, in this research, two segmentation methods of iris are suggested: Daugman method and Gupta method to investigate the feasibility of these segmentations in iris recognition. An enhanced method based on the techniques of the mentioned two methods is proposed, which can guarantee the accuracy of the iris identification system. The proposed method takes into account the elliptical shape of the pupil and iris. Eyelid detection is another step that has been included in this study as a part of segmentation stage. The dataset which is used for the study is CASIA v3 including the three subsets: Interval, Lamp and Twin. The performance measurement of the proposed method is done by determining the number of success images. The results of the study are very promising with an accuracy of 99.9% compared to the related existing methods. 2010 Thesis http://eprints.utm.my/id/eprint/16448/ http://eprints.utm.my/id/eprint/16448/1/MuadhShaifMohammedMFSKSM2010.pdf application/pdf en public masters Universiti Teknologi Malaysia, Faculty of Computer Science and Information System Faculty of Computer Science and Information System
institution	Universiti Teknologi Malaysia
collection	UTM Institutional Repository
language	English
topic	QA75 Electronic computers Computer science
spellingShingle	QA75 Electronic computers Computer science Mohammed Mukred, Muaadh Shaif A hybrid method for iris segmentation
description	Advance development in security technology has caused many major corporations and governments to start employing modern techniques in identifying the identity of the individuals. Among the common biometric identification methods are facial recognition, fingerprint recognition, speaker verification and so on, present a new solution for applications that require a high degree of security. Among these biometric methods, iris recognition becomes an important topic in pattern recognition, and it depends on the iris which is located in a place that still stable through human life. Furthermore, the probability to find two identical iris's approaching to zero value is quite easy. The identification system consists of several stages, and segmentation is the most crucial step. The current segmentation methods still have limitation in localizing the iris due to circular shape consideration of the pupil. Therefore, in this research, two segmentation methods of iris are suggested: Daugman method and Gupta method to investigate the feasibility of these segmentations in iris recognition. An enhanced method based on the techniques of the mentioned two methods is proposed, which can guarantee the accuracy of the iris identification system. The proposed method takes into account the elliptical shape of the pupil and iris. Eyelid detection is another step that has been included in this study as a part of segmentation stage. The dataset which is used for the study is CASIA v3 including the three subsets: Interval, Lamp and Twin. The performance measurement of the proposed method is done by determining the number of success images. The results of the study are very promising with an accuracy of 99.9% compared to the related existing methods.
format	Thesis
qualification_level	Master's degree
author	Mohammed Mukred, Muaadh Shaif
author_facet	Mohammed Mukred, Muaadh Shaif
author_sort	Mohammed Mukred, Muaadh Shaif
title	A hybrid method for iris segmentation
title_short	A hybrid method for iris segmentation
title_full	A hybrid method for iris segmentation
title_fullStr	A hybrid method for iris segmentation
title_full_unstemmed	A hybrid method for iris segmentation
title_sort	hybrid method for iris segmentation
granting_institution	Universiti Teknologi Malaysia, Faculty of Computer Science and Information System
granting_department	Faculty of Computer Science and Information System
publishDate	2010
url	http://eprints.utm.my/id/eprint/16448/1/MuadhShaifMohammedMFSKSM2010.pdf
_version_	1747815045240193024

A hybrid method for iris segmentation

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