Reflection removal and feature extraction techniques in non-cooperative visible eye images for iris recognition

Research on iris recognition system nowadays focuses on identifying a person in a non-cooperative environment by capturing an eye image in motion and at different distances. A visible wavelength illumination is used to capture the eye image which is believed to be safer to the eyes as excessive leve...

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Main Author:	Mat Raffei, Anis Farihan
Format:	Thesis
Language:	English
Published:	2013
Subjects:	TA Engineering (General) Civil engineering (General)
Online Access:	http://eprints.utm.my/id/eprint/41715/5/AnisFarihanMatRaffeiMFSKSM2013.pdf
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id	my-utm-ep.41715
record_format	uketd_dc
spelling	my-utm-ep.417152017-06-22T02:32:48Z Reflection removal and feature extraction techniques in non-cooperative visible eye images for iris recognition 2013-09 Mat Raffei, Anis Farihan TA Engineering (General). Civil engineering (General) Research on iris recognition system nowadays focuses on identifying a person in a non-cooperative environment by capturing an eye image in motion and at different distances. A visible wavelength illumination is used to capture the eye image which is believed to be safer to the eyes as excessive level of near infrared wavelength illumination can endanger the eye. However, the quality of data captured is very low and there are large reflections with different intensities in the eye image. These have caused incorrect segmentation of iris boundaries as well as the inability to extract texture features of an iris in a non-cooperative environment leading to a reduction in the iris recognition performance. The research proposed the development of two combined methods to improve the iris recognition system. The first combined method consists of line intensity profile and support vector machine and the second is a combination of multiscale sparse representation of local Radon transform. The former identifies and classifies between reflections and nonreflections whereas the latter performs three processes: reduces noise during down sample of normalized iris, extracts an iris texture in the different angles of orientation information and uses score combination of multiscale at the end of the process to increase the matching score. These two methods were tested against UBIRIS.v2 iris database and the results of iris recognition compared to the existing methods achieved an accuracy of more than 90%. 2013-09 Thesis http://eprints.utm.my/id/eprint/41715/ http://eprints.utm.my/id/eprint/41715/5/AnisFarihanMatRaffeiMFSKSM2013.pdf application/pdf en public masters Universiti Teknologi Malaysia, Faculty of Computing Faculty of Computing
institution	Universiti Teknologi Malaysia
collection	UTM Institutional Repository
language	English
topic	TA Engineering (General) Civil engineering (General)
spellingShingle	TA Engineering (General) Civil engineering (General) Mat Raffei, Anis Farihan Reflection removal and feature extraction techniques in non-cooperative visible eye images for iris recognition
description	Research on iris recognition system nowadays focuses on identifying a person in a non-cooperative environment by capturing an eye image in motion and at different distances. A visible wavelength illumination is used to capture the eye image which is believed to be safer to the eyes as excessive level of near infrared wavelength illumination can endanger the eye. However, the quality of data captured is very low and there are large reflections with different intensities in the eye image. These have caused incorrect segmentation of iris boundaries as well as the inability to extract texture features of an iris in a non-cooperative environment leading to a reduction in the iris recognition performance. The research proposed the development of two combined methods to improve the iris recognition system. The first combined method consists of line intensity profile and support vector machine and the second is a combination of multiscale sparse representation of local Radon transform. The former identifies and classifies between reflections and nonreflections whereas the latter performs three processes: reduces noise during down sample of normalized iris, extracts an iris texture in the different angles of orientation information and uses score combination of multiscale at the end of the process to increase the matching score. These two methods were tested against UBIRIS.v2 iris database and the results of iris recognition compared to the existing methods achieved an accuracy of more than 90%.
format	Thesis
qualification_level	Master's degree
author	Mat Raffei, Anis Farihan
author_facet	Mat Raffei, Anis Farihan
author_sort	Mat Raffei, Anis Farihan
title	Reflection removal and feature extraction techniques in non-cooperative visible eye images for iris recognition
title_short	Reflection removal and feature extraction techniques in non-cooperative visible eye images for iris recognition
title_full	Reflection removal and feature extraction techniques in non-cooperative visible eye images for iris recognition
title_fullStr	Reflection removal and feature extraction techniques in non-cooperative visible eye images for iris recognition
title_full_unstemmed	Reflection removal and feature extraction techniques in non-cooperative visible eye images for iris recognition
title_sort	reflection removal and feature extraction techniques in non-cooperative visible eye images for iris recognition
granting_institution	Universiti Teknologi Malaysia, Faculty of Computing
granting_department	Faculty of Computing
publishDate	2013
url	http://eprints.utm.my/id/eprint/41715/5/AnisFarihanMatRaffeiMFSKSM2013.pdf
_version_	1747816603125284864

Reflection removal and feature extraction techniques in non-cooperative visible eye images for iris recognition

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