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Segmentation-level fusion for iris recogntion

dc.contributor.authorWild, Peter
dc.contributor.authorHofbauer, Heinz
dc.contributor.authorFerryman, James
dc.contributor.authorUhl, Andreas
dc.contributor.editorBrömme, Arslan
dc.contributor.editorBusch, Christoph
dc.contributor.editorRathgeb, Christian
dc.contributor.editorUhl, Andreas
dc.date.accessioned2017-06-30T08:19:17Z
dc.date.available2017-06-30T08:19:17Z
dc.date.issued2015
dc.description.abstractThis paper investigates the potential of fusion at normalisation/segmentation level prior to feature extraction. While there are several biometric fusion methods at data/feature level, score level and rank/decision level combining raw biometric signals, scores, or ranks/decisions, this type of fusion is still in its infancy. However, the increasing demand to allow for more relaxed and less invasive recording conditions, especially for on-the-move iris recognition, suggests to further investigate fusion at this very low level. This paper focuses on the approach of multi-segmentation fusion for iris biometric systems investigating the benefit of combining the segmentation result of multiple normalisation algorithms, using four methods from two different public iris toolkits (USIT, OSIRIS) on the public CASIA and IITD iris datasets. Evaluations based on recognition accuracy and ground truth segmentation data indicate high sensitivity with regards to the type of errors made by segmentation algorithms.en
dc.identifier.isbn978-3-88579-639-8
dc.identifier.pissn1617-5468
dc.language.isoen
dc.publisherGesellschaft für Informatik e.V.
dc.relation.ispartofBIOSIG 2015
dc.relation.ispartofseriesLecture Notes in Informatics (LNI) - Proceedings, Volume P-245
dc.titleSegmentation-level fusion for iris recogntionen
dc.typeText/Conference Paper
gi.citation.endPage72
gi.citation.publisherPlaceBonn
gi.citation.startPage61
gi.conference.date9.-11. September 2015
gi.conference.locationDarmstadt

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