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dc.contributor.authorSchuiki, Johannes
dc.contributor.authorUhl, Andreas
dc.contributor.editorBrömme, Arslan
dc.contributor.editorBusch, Christoph
dc.contributor.editorDantcheva, Antitza
dc.contributor.editorRaja, Kiran
dc.contributor.editorRathgeb, Christian
dc.contributor.editorUhl, Andreas
dc.date.accessioned2020-09-16T08:25:49Z
dc.date.available2020-09-16T08:25:49Z
dc.date.issued2020
dc.identifier.isbn978-3-88579-700-5
dc.identifier.issn1617-5468
dc.identifier.urihttp://dl.gi.de/handle/20.500.12116/34345
dc.description.abstractIn this study, a previously published infrared finger vein liveness detection scheme is tested for its applicability on dorsal hand vein videos. A custom database consisting of five different types of presentation attacks recorded with transillumination as well as reflected light illumination is examined. Additionally, two different methods for liveness detection are presented in this work. All methods described employ the concept of generating a signal through the change in average pixel illumination, which is referred to as Photoplethysmography. Feature vectors in order to classify a given video sequence are generated using spectral analysis of the time series. Experimental results show the effectiveness of the proposed methods.en
dc.language.isoen
dc.publisherGesellschaft für Informatik e.V.
dc.relation.ispartofBIOSIG 2020 - Proceedings of the 19th International Conference of the Biometrics Special Interest Group
dc.relation.ispartofseriesLecture Notes in Informatics (LNI) - Proceedings, Volume P-306
dc.subjectnear infrared
dc.subjectliveness detection
dc.subjectpresentation attack detection
dc.subjectphotoplethysmography
dc.subjectdorsal hand vein
dc.subjectvideo sequence
dc.titleImproved Liveness Detection in Dorsal Hand Vein Videos using Photoplethysmographyen
dc.typeText/Conference Paper
dc.pubPlaceBonn
mci.reference.pages57-65
mci.conference.sessiontitleRegular Research Papers
mci.conference.locationInternational Digital Conference
mci.conference.date16.-18. September 2020


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