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Simulation of Print-Scan Transformations for Face Images based on Conditional Adversarial Networks

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dc.contributor.authorMitkovski, Aleksandar
dc.contributor.authorMerkle, Johannes
dc.contributor.authorRathgeb, Christian
dc.contributor.authorTams, Benjamin
dc.contributor.authorBernardo, Kevin
dc.contributor.authorHaryanto, Nathania E.
dc.contributor.authorBusch, Christoph
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.accessioned2020-09-16T08:25:50Z
dc.date.available2020-09-16T08:25:50Z
dc.date.issued2020
dc.description.abstractIn many countries, printing and scanning of face images is frequently performed as part of the issuance process of electronic travel documents, e.g., ePassports. Image alterations induced by such print-scan transformations may negatively effect the performance of various biometric subsystems, in particular image manipulation detection. Consequently, according training data is needed in order to achieve robustness towards said transformations. However, manual printing and scanning is time-consuming and costly. In this work, we propose a simulation of print-scan transformations for face images based on a Conditional Generative Adversarial Network (cGAN). To this end, subsets of two public face databases are manually printed and scanned using different printer-scanner combinations. A cGAN is then trained to perform an image-to-image translation which simulates the corresponding print-scan transformations. The goodness of simulation is evaluated with respect to image quality, biometric sample quality and performance, as well as human assessment.en
dc.identifier.isbn978-3-88579-700-5
dc.identifier.pissn1617-5468
dc.identifier.urihttps://dl.gi.de/handle/20.500.12116/34347
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.subjectBiometrics
dc.subjectface
dc.subjectprint-scan transformation
dc.subjectsimulation
dc.subjectgenerative adversarial network
dc.titleSimulation of Print-Scan Transformations for Face Images based on Conditional Adversarial Networksen
dc.typeText/Conference Paper
gi.citation.endPage86
gi.citation.publisherPlaceBonn
gi.citation.startPage77
gi.conference.date16.-18. September 2020
gi.conference.locationInternational Digital Conference
gi.conference.sessiontitleRegular Research Papers

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P306 - BIOSIG 2020 - Proceedings of the 19th International Conference of the Biometrics Special Interest Group