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Style Your Face Morph and Improve Your Face Morphing Attack Detector

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dc.contributor.authorSeibold, Clemens
dc.contributor.authorHilsmann, Anna
dc.contributor.authorEisert, Peter
dc.contributor.editorBrömme, Arslan
dc.contributor.editorBusch, Christoph
dc.contributor.editorDantcheva, Antitza
dc.contributor.editorRathgeb, Christian
dc.contributor.editorUhl, Andreas
dc.date.accessioned2020-09-15T13:01:30Z
dc.date.available2020-09-15T13:01:30Z
dc.date.issued2019
dc.description.abstractA morphed face image is a synthetically created image that looks so similar to the faces of two subjects that both can use it for verification against a biometric verification system. It can be easily created by aligning and blending face images of the two subjects. In this paper, we propose a style transfer based method that improves the quality of morphed face images. It counters the image degeneration during the creation of morphed face images caused by blending. We analyze different state of the art face morphing attack detection systems regarding their performance against our improved morphed face images and other methods that improve the image quality. All detection systems perform significantly worse, when first confronted with our improved morphed face images. Most of them can be enhanced by adding our quality improved morphs to the training data, which further improves the robustness against other means of quality improvement.en
dc.identifier.isbn978-3-88579-690-9
dc.identifier.pissn1617-5468
dc.identifier.urihttps://dl.gi.de/handle/20.500.12116/34237
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.subjectbiometric spoofing
dc.subjectface morphing detection
dc.subjectimage quality improvement
dc.titleStyle Your Face Morph and Improve Your Face Morphing Attack Detectoren
dc.typeText/Conference Paper
gi.citation.endPage45
gi.citation.publisherPlaceBonn
gi.citation.startPage35
gi.conference.date18.-20. September 2019
gi.conference.locationDarmstadt, Germany
gi.conference.sessiontitleRegular Research Papers

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P296 - BIOSIG 2019 - Proceedings of the 18th International Conference of the Biometrics Special Interest Group