Iris recognition system by using support vector machines

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Main Authors:	Hasimah, Ali, Momoh, J. E. Salami, Wahyudi
Other Authors:	hashimah@unimap.edu.my
Format:	Working Paper
Language:	English
Published:	Institute of Electrical and Electronics Engineers (IEEE) 2009
Subjects:	Biometrics (Access control) Support vector machines Image recognition Feature extraction Iris recognition Biometric systems
Online Access:	http://dspace.unimap.edu.my/xmlui/handle/123456789/7403
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Institution:	Universiti Malaysia Perlis
Language:	English

id	my.unimap-7403
record_format	dspace
spelling	my.unimap-74032010-11-24T02:21:43Z Iris recognition system by using support vector machines Hasimah, Ali Momoh, J. E. Salami Wahyudi hashimah@unimap.edu.my Biometrics (Access control) Support vector machines Image recognition Feature extraction Iris recognition Biometric systems Link to publisher's homepage at http://ieeexplore.ieee.org In recent years, with the increasing demands of security in our networked society, biometric systems for user verification are becoming more popular. Iris recognition system is a new technology for user verification. In this paper, the CASIA iris database is used for individual user's verification by using support vector machines (SVMs) which based on the analysis of iris code as feature extraction is discussed. This feature is then used to recognize authentic users and to reject impostors. Support Vector Machines (SVMs) technique was used for the classification process. The proposed method is evaluated based upon False Rejection Rate (FRR) and False Acceptance Rate (FAR) and the experimental result show that this technique produces good performance. 2009-12-11T07:40:05Z 2009-12-11T07:40:05Z 2008-05-13 Working Paper p.516-521 978-1-4244-1691-2 http://ieeexplore.ieee.org/xpls/abs_all.jsp?=&arnumber=4580657 http://hdl.handle.net/123456789/7403 en Proceedings of the International Conference on Computer and Communication Engineering (ICCCE08) Institute of Electrical and Electronics Engineers (IEEE)
institution	Universiti Malaysia Perlis
building	UniMAP Library
collection	Institutional Repository
continent	Asia
country	Malaysia
content_provider	Universiti Malaysia Perlis
content_source	UniMAP Library Digital Repository
url_provider	http://dspace.unimap.edu.my/
language	English
topic	Biometrics (Access control) Support vector machines Image recognition Feature extraction Iris recognition Biometric systems
spellingShingle	Biometrics (Access control) Support vector machines Image recognition Feature extraction Iris recognition Biometric systems Hasimah, Ali Momoh, J. E. Salami Wahyudi Iris recognition system by using support vector machines
description	Link to publisher's homepage at http://ieeexplore.ieee.org
author2	hashimah@unimap.edu.my
author_facet	hashimah@unimap.edu.my Hasimah, Ali Momoh, J. E. Salami Wahyudi
format	Working Paper
author	Hasimah, Ali Momoh, J. E. Salami Wahyudi
author_sort	Hasimah, Ali
title	Iris recognition system by using support vector machines
title_short	Iris recognition system by using support vector machines
title_full	Iris recognition system by using support vector machines
title_fullStr	Iris recognition system by using support vector machines
title_full_unstemmed	Iris recognition system by using support vector machines
title_sort	iris recognition system by using support vector machines
publisher	Institute of Electrical and Electronics Engineers (IEEE)
publishDate	2009
url	http://dspace.unimap.edu.my/xmlui/handle/123456789/7403
_version_	1643788804824236032

Iris recognition system by using support vector machines

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