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dc.contributor.authorBylappa Raja, Kiran
dc.contributor.authorRamachandra, Raghavendra
dc.contributor.authorBusch, Christoph
dc.date.accessioned2019-12-05T09:22:38Z
dc.date.available2019-12-05T09:22:38Z
dc.date.created2019-05-06T14:51:47Z
dc.date.issued2019
dc.identifier.citationLecture Notes in Computer Science. 2019, 11188 LNCS 103-116.nb_NO
dc.identifier.issn0302-9743
dc.identifier.urihttp://hdl.handle.net/11250/2631881
dc.description.abstractPeriocular characteristics is gaining prominence in biometric systems and surveillance systems that operate either in NIR spectrum or visible spectrum. While the ocular information can be well utilized, there exists a challenge to compare images from different spectra such as Near-Infra-Red (NIR) versus Visible spectrum (VIS). In addition, the ocular biometric templates from both NIR and VIS domain need to be protected after the extraction of features to avoid the leakage or linkability of biometric data. In this work, we explore a new approach based on anchored kernel hashing to obtain a cancelable biometric template that is both discriminative for recognition purposes while preserving privacy. The key benefit is that the proposed approach not only works for both NIR and the Visible spectrum, it can also be used with good accuracy for cross-spectral protected template comparison. Through the set of experiments using a cross-spectral periocular database, we demonstrate the performance with EER=1.39% and EER=1.61% for NIR and VIS protected templates respectively. We further present a set of cross-spectral template comparison by comparing the protected templates from one spectrum to another spectra to demonstrate the applicability of the proposed approach.nb_NO
dc.language.isoengnb_NO
dc.publisherSpringernb_NO
dc.titleAnchored kernel hashing for cancelable template protection for cross-spectral periocular datanb_NO
dc.typeJournal articlenb_NO
dc.typePeer reviewednb_NO
dc.description.versionacceptedVersionnb_NO
dc.source.pagenumber103-116nb_NO
dc.source.volume11188 LNCSnb_NO
dc.source.journalLecture Notes in Computer Sciencenb_NO
dc.identifier.doi10.1007/978-3-030-05792-3_10
dc.identifier.cristin1695850
dc.relation.projectNorges forskningsråd: 248030nb_NO
dc.description.localcodeThis is a post-peer-review, pre-copyedit version of an article published in Lecture Notes in Computer Science. Locked until 19 December 2019 due to copyright restrictions. The final authenticated version is available online at: https://doi.org/10.1007/978-3-030-05792-3_10.nb_NO
cristin.unitcode194,63,30,0
cristin.unitnameInstitutt for informasjonssikkerhet og kommunikasjonsteknologi
cristin.ispublishedtrue
cristin.fulltextpostprint
cristin.qualitycode1


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