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dc.contributor.authorLinortner, Michael
dc.contributor.authorUhl, Andreas
dc.contributor.editorBrömme, Arslan
dc.contributor.editorBusch, Christoph
dc.contributor.editorDamer, Naser
dc.contributor.editorDantcheva, Antitza
dc.contributor.editorGomez-Barrero, Marta
dc.contributor.editorRaja, Kiran
dc.contributor.editorRathgeb, Christian
dc.contributor.editorSequeira, Ana
dc.contributor.editorUhl, Andreas
dc.date.accessioned2021-10-04T08:43:48Z
dc.date.available2021-10-04T08:43:48Z
dc.date.issued2021
dc.identifier.isbn978-3-88579-709-8
dc.identifier.issn1617-5468
dc.identifier.urihttp://dl.gi.de/handle/20.500.12116/37462
dc.description.abstractVein recognition usually uses binary features, but besides deep learning-based approaches key-point and minutiae-based ones started to become popular as well. Statistical measures for vein minutiae points, like spatial point distribution, have not been investigated in literature so far. In this work the number of vein minutiae points and their spatial distribution is analyzed in relation to recognition accuracy. The goal is to initiate a discussion on statistical behavior of vein minutiae points and deriving possible quality measures for vein minutiae point sets.en
dc.language.isoen
dc.publisherGesellschaft für Informatik e.V.
dc.relation.ispartofBIOSIG 2021 - Proceedings of the 20th International Conference of the Biometrics Special Interest Group
dc.relation.ispartofseriesLecture Notes in Informatics (LNI) - Proceedings, Volume P-325
dc.subjectVein recognition
dc.subjectvein minutiae distribution
dc.subjectspatial point distribution
dc.titleOn the Relevance of Minutiae Count and Distribution for Finger Vein Recognition Accuracyen
dc.typeText/Conference Paper
dc.pubPlaceBonn
mci.reference.pages253-260
mci.conference.sessiontitleFurther Conference Contributions
mci.conference.locationInternational Digital Conference
mci.conference.date15.-17. September 2021


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