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Fusion of Face Demorphing and Deep Face Representations for Differential Morphing Attack Detection

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dc.contributor.authorShiqerukaj, Elidona
dc.contributor.authorRathgeb, Christian
dc.contributor.authorMerkle, Johannes
dc.contributor.authorDrozdowski, Pawel
dc.contributor.authorTams, Benjamin
dc.contributor.editorBrömme, Arslan
dc.contributor.editorDamer, Naser
dc.contributor.editorGomez-Barrero, Marta
dc.contributor.editorRaja, Kiran
dc.contributor.editorRathgeb, Christian
dc.contributor.editorSequeira Ana F.
dc.contributor.editorTodisco, Massimiliano
dc.contributor.editorUhl, Andreas
dc.date.accessioned2022-10-27T10:19:26Z
dc.date.available2022-10-27T10:19:26Z
dc.date.issued2022
dc.description.abstractAlgorithm fusion is frequently employed to improve the accuracy of pattern recognition tasks. This particularly applies to biometrics including attack detection mechanisms. In this work, we apply a fusion of two differential morphing attack detection methods, i.e. Demorphing and Deep Face Representations. Experiments are performed in a cross-database scenario using high-quality face morphs along with realistic live captures. Obtained results reveal that a weighted sum-based score-level fusion of Demorphing and Deep Face Representations improves the morphing attack detection accuracy. With the proposed fusion, a detection equal error rate of 4.9% is achieved, compared to detection equal error rates of 5.6% and 5.8% of the best individual morphing attack detection methods, respectively.en
dc.identifier.doi10.1109/BIOSIG55365.2022.9897023
dc.identifier.isbn978-3-88579-723-4
dc.identifier.pissn1617-5481
dc.identifier.urihttps://dl.gi.de/handle/20.500.12116/39690
dc.language.isoen
dc.publisherGesellschaft für Informatik e.V.
dc.relation.ispartofBIOSIG 2022
dc.relation.ispartofseriesLecture Notes in Informatics (LNI) - Proceedings, Volume P-329
dc.subjectFace recognition
dc.subjectmorphing attack detection
dc.subjectfusion
dc.subjectdemorphing
dc.subjectdeep face representations
dc.titleFusion of Face Demorphing and Deep Face Representations for Differential Morphing Attack Detectionen
dc.typeText/Conference Paper
gi.citation.endPage149
gi.citation.publisherPlaceBonn
gi.citation.startPage141
gi.conference.date14.-16. September 2022
gi.conference.locationDarmstadt
gi.conference.sessiontitleRegular Research Papers

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P329 - BIOSIG 2022 - Proceedings of the 21st International Conference of the Biometrics Special Interest Group