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dc.contributor.authorAyu Fitrie Haziqah, Sallehuddin-
dc.contributor.authorMuhammad Imran, Ahmad-
dc.contributor.authorRuzelita, Ngadiran-
dc.contributor.authorMohd Nazrin, Md Isa-
dc.date.accessioned2019-12-03T04:23:24Z-
dc.date.available2019-12-03T04:23:24Z-
dc.date.issued2016-
dc.identifier.citationJournal of Telecommunication, Electronic and Computer Engineering, vol.8(4), 2016, 133-138en_US
dc.identifier.issn2180–1843-
dc.identifier.issn2289-8131 (online)-
dc.identifier.urihttp://dspace.unimap.edu.my:80/xmlui/handle/123456789/63563-
dc.descriptionLink to publisher's homepage at http://journal.utem.edu.myen_US
dc.description.abstractThe uniqueness of iris texture makes it one of the reliable physiological biometric traits compare to the other biometric traits. In this paper, we investigate a different level of fusion approach in iris image. Although, a number of iris recognition methods has been proposed in recent years, however most of them focus on the feature extraction and classification method. Less number of method focuses on the information fusion of iris images. Fusion is believed to produce a better discrimination power in the feature space, thus we conduct an analysis to investigate which fusion level is able to produce the best result for iris recognition system. Experimental analysis using CASIA dataset shows feature level fusion produce 99% recognition accuracy. The verification analysis shows the best result is GAR = 95% at the FRR = 0.1%.en_US
dc.language.isoenen_US
dc.publisherUniversiti Teknikal Malaysia Melakaen_US
dc.subjectBiometric systemen_US
dc.subjectIris recognitionen_US
dc.subjectInformation fusionen_US
dc.titleA survey of iris recognition systemen_US
dc.typeArticleen_US
dc.identifier.urljournal.utem.edu.my/index.php/jtec/article/view/1188-
dc.contributor.urlm.imran@unimap.edu.my-
Appears in Collections:School of Computer and Communication Engineering (Articles)

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