Logo des Repositoriums
 

Vein Enhancement with Deep Auto-Encoders to improve Finger Vein Recognition

dc.contributor.authorBros, Victor
dc.contributor.authorKotwal, Ketan
dc.contributor.authorMarcel, Sébastien
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.accessioned2021-10-04T08:43:49Z
dc.date.available2021-10-04T08:43:49Z
dc.date.issued2021
dc.description.abstractThe field of Vascular Biometric Recognition has drawn a lot of attention recently with the emergence of new computer vision techniques. The different methods using Deep Learning involve a new understanding of deeper features from the vascular network. The specific architecture of the veins needs complex model capable of comprehending the vascular pattern. In this paper, we present an image enhancement method using Deep Convolutional Neural Network. For this task, a residual convolutional auto-encoder architecture has been trained in a supervised way to enhance the vein patterns in near-infrared images. The method has been evaluated on several databases with promising results on the UTFVP database as a main result. In including the model as a preprocessing in the biometric pipelines of recognition for finger vein patterns, the error rate has been reduced from 2.1% to 1.0%.en
dc.identifier.isbn978-3-88579-709-8
dc.identifier.pissn1617-5468
dc.identifier.urihttps://dl.gi.de/handle/20.500.12116/37463
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-326
dc.subjectFinger Vein Recognition
dc.subjectDeep Residual Convolutional Auto-Encoder
dc.subjectVein Enhancement
dc.titleVein Enhancement with Deep Auto-Encoders to improve Finger Vein Recognitionen
dc.typeText/Conference Paper
gi.citation.endPage268
gi.citation.publisherPlaceBonn
gi.citation.startPage261
gi.conference.date15.-17. September 2021
gi.conference.locationInternational Digital Conference
gi.conference.sessiontitleFurther Conference Contributions

Dateien

Originalbündel
1 - 1 von 1
Lade...
Vorschaubild
Name:
biosig2021_proceedings_28.pdf
Größe:
169.85 KB
Format:
Adobe Portable Document Format