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Image metric-based biometric comparators: a supplement to feature vector-based Hamming distance?

dc.contributor.authorHofbauer, Heinz
dc.contributor.authorRathgeb, Christian
dc.contributor.authorUhl, Andreas
dc.contributor.authorWild, Peter
dc.contributor.editorBrömme, Arslan
dc.contributor.editorBusch, Christoph
dc.date.accessioned2018-11-19T13:16:42Z
dc.date.available2018-11-19T13:16:42Z
dc.date.issued2012
dc.description.abstractIn accordance with the ISO/IEC FDIS 19794-6 standard an iris-biometric fusion of image metric-based and Hamming distance (HD) comparison scores is presented. In order to demonstrate the applicability of a knowledge transfer from image quality assessment to iris recognition, Peak Signal to Noise Ratio (PSNR), Structural Similarity Index Measure (SSIM), Local Edge Gradients metric (LEG), Edge Similarity Score (ESS), Local Feature Based Visual Security (LFBVS), and Visual Information Fidelity (VIF) are applied to iris textures, i.e. query textures are interpreted as noisy representations of registered ones. Obtained scores are fused with traditional HD scores obtained from iris-codes generated by different feature extraction algorithms. Experimental evaluations on the CASIA-v3 iris database confirm the soundness of the proposed approach.en
dc.identifier.isbn978-3-88579-290-1
dc.identifier.pissn1617-5468
dc.identifier.urihttps://dl.gi.de/handle/20.500.12116/18322
dc.language.isoen
dc.publisherGesellschaft für Informatik e.V.
dc.relation.ispartofBIOSIG 2012
dc.relation.ispartofseriesLecture Notes in Informatics (LNI) - Proceedings, Volume P-196
dc.titleImage metric-based biometric comparators: a supplement to feature vector-based Hamming distance?en
dc.typeText/Conference Paper
gi.citation.endPage85
gi.citation.publisherPlaceBonn
gi.citation.startPage75
gi.conference.date06.-07. September 2012
gi.conference.locationDarmstadt
gi.conference.sessiontitleRegular Research Papers

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