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Improving Fingerprint Alteration Detection
University of Göttingen, Göttingen, Germany.
Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR - Center for Applied Intelligent Systems Research.
Norwegian Biometrics Laboratory, Gjøvik University College, Gjøvik, Norway.
Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR - Center for Applied Intelligent Systems Research.ORCID iD: 0000-0002-4929-1262
Show others and affiliations
2015 (English)In: 2015 9th International Symposium on Image and Signal Processing and Analysis (ISPA) / [ed] Sven Lončarić, Dick Lerski, Hannu Eskola, Robert Bregović, Zagreb: University of Zagreb , 2015, 83-86 p.Conference paper, Published paper (Refereed)
Abstract [en]

Fingerprint alteration is a type of presentation attack in which the attacker strives to avoid identification, e.g. at border control or in forensic investigations. As a countermeasure, fingerprint alteration detection aims to automatically discover the occurrence of such attacks by classifying fingerprint images as ’normal’ or ’altered’. In this paper, we propose four new features for improving the performance of fingerprint alteration detection modules. We evaluate the usefulness of these features on a benchmark and compare them to four existing features from the literature. © Copyright 2015 IEEE - All rights reserved.

Place, publisher, year, edition, pages
Zagreb: University of Zagreb , 2015. 83-86 p.
Series
International Symposium on Image and Signal Processing and Analysis, ISSN 1849-2266 ; 9
Keyword [en]
biometrics, fingerprints
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
URN: urn:nbn:se:hh:diva-29447DOI: 10.1109/ISPA.2015.7306037ISI: 000378419400015Scopus ID: 2-s2.0-84978519672ISBN: 978-1-4673-8032-4 ISBN: 978-1-4673-8031-7 OAI: oai:DiVA.org:hh-29447DiVA: diva2:853384
Conference
9th International Symposium on Image and Signal Processing and Analysis, Zagreb, Croatia, September 7-9, 2015
Projects
INGRESS
Funder
EU, FP7, Seventh Framework Programme, SEC-2012-312792
Note

This work is carried out under the funding of the EU-FP7 INGRESS project (Grant No. SEC-2012-312792). C. Gottschlich also acknowledges the support of the Felix-Bernstein-Institute for Mathematical Statistics in the Bio-sciences and the Niedersachsen Vorab of the Volkswagen Foundation.

Available from: 2015-09-13 Created: 2015-09-13 Last updated: 2017-09-27Bibliographically approved

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