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Towards mobile and touchless fingerprint verification

: Jonietz, Christof; Monari, Eduardo; Widak, Heiko; Qu, C.

Postprint urn:nbn:de:0011-n-3601562 (2.2 MByte PDF)
MD5 Fingerprint: be2e9bb37e283e66c30d6c58d26a2b15
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Erstellt am: 22.9.2015

Institute of Electrical and Electronics Engineers -IEEE-; IEEE Signal Processing Society; IEEE Computer Society; Karlsruher Institut für Technologie -KIT-:
12th IEEE International Conference on Advanced Video and Signal-Based Surveillance, AVSS 2015 : Karlsruhe, Germany, 25-28 August 2015; Including workshop papers
Piscataway, NJ: IEEE, 2015
ISBN: 978-1-4673-7633-4
ISBN: 978-1-4673-7632-7
International Conference on Advanced Video and Signal-Based Surveillance (AVSS) <12, 2015, Karlsruhe>
International Workshop on Identification and Surveillance for Border Control (ISBC) <1, 2015, Karlsruhe>
Konferenzbeitrag, Elektronische Publikation
Fraunhofer IOSB ()

Touchless finger detection for the biometric fingerprint verification/identification process with mobile devices is considered in this paper. Fingerprint capturing is based on a camera system with bright-field illumination. For finger detection, a machine learning based algorithm with Aggregated Channel Features (ACFs) and a skin-color based finger segmentation with a geometric shape based approach for fingertip detection are considered, respectively. Results demonstrate the performance of both algorithms.