Publica
Hier finden Sie wissenschaftliche Publikationen aus den Fraunhofer-Instituten. Towards mobile and touchless fingerprint verification
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Postprint urn:nbn:de:0011-n-3601562 (2.2 MByte PDF) MD5 Fingerprint: be2e9bb37e283e66c30d6c58d26a2b15 © IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE. 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
S.168-173 |
| 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> |
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| Englisch |
| Konferenzbeitrag, Elektronische Publikation |
| Fraunhofer IOSB () |
Abstract
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.