Fusion of Face Demorphing and Deep Face Representations for Differential Morphing Attack Detection
| dc.contributor.author | Shiqerukaj, Elidona | |
| dc.contributor.author | Rathgeb, Christian | |
| dc.contributor.author | Merkle, Johannes | |
| dc.contributor.author | Drozdowski, Pawel | |
| dc.contributor.author | Tams, Benjamin | |
| dc.contributor.editor | Brömme, Arslan | |
| dc.contributor.editor | Damer, Naser | |
| dc.contributor.editor | Gomez-Barrero, Marta | |
| dc.contributor.editor | Raja, Kiran | |
| dc.contributor.editor | Rathgeb, Christian | |
| dc.contributor.editor | Sequeira Ana F. | |
| dc.contributor.editor | Todisco, Massimiliano | |
| dc.contributor.editor | Uhl, Andreas | |
| dc.date.accessioned | 2022-10-27T10:19:26Z | |
| dc.date.available | 2022-10-27T10:19:26Z | |
| dc.date.issued | 2022 | |
| dc.description.abstract | Algorithm 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.doi | 10.1109/BIOSIG55365.2022.9897023 | |
| dc.identifier.isbn | 978-3-88579-723-4 | |
| dc.identifier.pissn | 1617-5481 | |
| dc.identifier.uri | https://dl.gi.de/handle/20.500.12116/39690 | |
| dc.language.iso | en | |
| dc.publisher | Gesellschaft für Informatik e.V. | |
| dc.relation.ispartof | BIOSIG 2022 | |
| dc.relation.ispartofseries | Lecture Notes in Informatics (LNI) - Proceedings, Volume P-329 | |
| dc.subject | Face recognition | |
| dc.subject | morphing attack detection | |
| dc.subject | fusion | |
| dc.subject | demorphing | |
| dc.subject | deep face representations | |
| dc.title | Fusion of Face Demorphing and Deep Face Representations for Differential Morphing Attack Detection | en |
| dc.type | Text/Conference Paper | |
| gi.citation.endPage | 149 | |
| gi.citation.publisherPlace | Bonn | |
| gi.citation.startPage | 141 | |
| gi.conference.date | 14.-16. September 2022 | |
| gi.conference.location | Darmstadt | |
| gi.conference.sessiontitle | Regular Research Papers |
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