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dc.contributor.authorDrozdowski, Pawel
dc.contributor.authorRathgeb, Christian
dc.contributor.authorBusch, Christoph
dc.date.accessioned2019-06-07T12:10:34Z
dc.date.available2019-06-07T12:10:34Z
dc.date.created2019-05-09T13:16:58Z
dc.date.issued2019
dc.identifier.citationIEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). 2019nb_NO
dc.identifier.isbn978-1-4799-8131-1
dc.identifier.urihttp://hdl.handle.net/11250/2600348
dc.description.abstractIn recent years, morphing of facial images has arisen as an important attack vector on biometric systems. Detection of morphed images has proven challenging for automated systems and human experts alike. Likewise, in recent years, the importance of efficient (fast) biometric identification has been emphasised by the rapid rise and growth of large-scale biometric systems around the world. In this paper, the aforementioned, hitherto unrelated, topics within the biometrics domain are combined: the properties of morphed images are exploited for the purpose of improving the transaction times of a biometric identification system. Specifically, morphs of two or more samples are used in the pre-selection step of a two-stage biometric identification system. In a proof-of-concept experimental evaluation using two state-of-the-art open-source facial recognition frameworks it is shown, that the proposed system achieves hit rates comparable to that of an exhaustive search-based baseline, while significantly reducing the penetration rate (and thus the computational workload) associated with the biometric identification transactions.nb_NO
dc.description.abstractTurning a vulnerability into an asset: Accelerating Facial Identification with Morphingnb_NO
dc.language.isoengnb_NO
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE)nb_NO
dc.relation.ispartof2019 IEEE International Conference on Acoustics, Speech, and Signal Processing
dc.titleTurning a vulnerability into an asset: Accelerating Facial Identification with Morphingnb_NO
dc.typeConference objectnb_NO
dc.typePeer reviewednb_NO
dc.description.versionacceptedVersionnb_NO
dc.source.pagenumber2582-2586nb_NO
dc.identifier.doi10.1109/ICASSP.2019.8683326
dc.identifier.cristin1696638
dc.description.localcode© 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.nb_NO
cristin.unitcode194,63,30,0
cristin.unitnameInstitutt for informasjonssikkerhet og kommunikasjonsteknologi
cristin.ispublishedtrue
cristin.fulltextpostprint
cristin.qualitycode1


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