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Multi-algorithm Benchmark for Fingerprint Presentation Attack Detection with Laser Speckle Contrast Imaging

dc.contributor.authorKolberg, Jascha
dc.contributor.authorGomez-Barrero, Marta
dc.contributor.authorBusch, Christoph
dc.contributor.editorBrömme, Arslan
dc.contributor.editorBusch, Christoph
dc.contributor.editorDantcheva, Antitza
dc.contributor.editorRathgeb, Christian
dc.contributor.editorUhl, Andreas
dc.date.accessioned2020-09-15T13:01:24Z
dc.date.available2020-09-15T13:01:24Z
dc.date.issued2019
dc.description.abstractThe increased usage of biometric authentication systems has raised concerns regarding the security of components in a biometric system. As a consequence, preventing security issues related to presentation attacks targeting the biometric capture device are of utmost importance. To develop presentation attack detection (PAD) mechanisms, features confirming the liveness of the biometric characteristic such as the blood flow within the finger are needed. Utilising laser speckle contrast imaging (LSCI) to observe blood movement below the surface, we present an evaluation of different machine learning classifiers for fingerprint PAD. The experiments over a database comprising 35 different presentation attack instrument (PAI) species show that the detection performance varies depending on the utilised feature extraction method. A majority voting of selected classifiers and features achieves an APCER of 9% for a convenient BPCER of 0.05%.en
dc.identifier.isbn978-3-88579-690-9
dc.identifier.pissn1617-5468
dc.identifier.urihttps://dl.gi.de/handle/20.500.12116/34222
dc.language.isoen
dc.publisherGesellschaft für Informatik e.V.
dc.relation.ispartofBIOSIG 2019 - Proceedings of the 18th International Conference of the Biometrics Special Interest Group
dc.relation.ispartofseriesLecture Notes in Informatics (LNI) - Proceedings, Volume P-297
dc.subjectPresentation Attack Detection
dc.subjectFingerprint
dc.subjectLSCI.
dc.titleMulti-algorithm Benchmark for Fingerprint Presentation Attack Detection with Laser Speckle Contrast Imagingen
dc.typeText/Conference Paper
gi.citation.endPage128
gi.citation.publisherPlaceBonn
gi.citation.startPage119
gi.conference.date18.-20. September 2019
gi.conference.locationDarmstadt, Germany
gi.conference.sessiontitleRegular Research Papers

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