Please use this identifier to cite or link to this item: http://dspace.unimap.edu.my:80/xmlui/handle/123456789/6613
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dc.contributor.authorAli, H.-
dc.contributor.authorSalami, M.J.E-
dc.contributor.authorWahyudi-
dc.date.accessioned2009-07-29T08:27:20Z-
dc.date.available2009-07-29T08:27:20Z-
dc.date.issued2008-
dc.identifier.citationp. 516-521en_US
dc.identifier.issn4580620-
dc.identifier.urihttp://ieeexplore.ieee.org/xpls/abs_all.jsp?=&arnumber=4580657-
dc.identifier.urihttp://dspace.unimap.edu.my/123456789/6613-
dc.descriptionLink to publisher's homepage at http://ieeexplore.ieee.orgen_US
dc.description.abstractIn 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.en_US
dc.language.isoenen_US
dc.publisherInstitute of Electrical and Electronics Engineering (IEEE)en_US
dc.relation.ispartofseriesProceedings of the International Conference on Computer and Communication Engineering 2008 (ICCCE08)en_US
dc.subjectLearning systemsen_US
dc.subjectVectorsen_US
dc.subjectBiometric systemsen_US
dc.subjectIris codeen_US
dc.subjectIris recognitionen_US
dc.subjectSupport vector machinesen_US
dc.subjectIris detectionen_US
dc.subjectImage processingen_US
dc.titleIris recognition system by using support vector machinesen_US
dc.typeArticleen_US
Appears in Collections:School of Mechatronic Engineering (Articles)

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