Fingerprint Class Recognition for Securing EMV Transaction

B. Vibert, J. M. Le Bars, C. Rosenberger, C. Charrier


Fingerprint analysis is a very important issue in biometry. The minutiae representation of a fingerprint is the most used modality to identify people or authorize access when using a biometric system. In this paper, we propose some features based on triangle parameters from the Delaunay triangulation of minutiae. We show the benefit of these features to recognize the type of a fingerprint without any access to the associated fingerprint image.


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Paper Citation

in Harvard Style

Vibert B., M. Le Bars J., Rosenberger C. and Charrier C. (2017). Fingerprint Class Recognition for Securing EMV Transaction . In Proceedings of the 3rd International Conference on Information Systems Security and Privacy - Volume 1: ICISSP, ISBN 978-989-758-209-7, pages 403-410. DOI: 10.5220/0006205704030410

in Bibtex Style

author={B. Vibert and J. M. Le Bars and C. Rosenberger and C. Charrier},
title={Fingerprint Class Recognition for Securing EMV Transaction},
booktitle={Proceedings of the 3rd International Conference on Information Systems Security and Privacy - Volume 1: ICISSP,},

in EndNote Style

JO - Proceedings of the 3rd International Conference on Information Systems Security and Privacy - Volume 1: ICISSP,
TI - Fingerprint Class Recognition for Securing EMV Transaction
SN - 978-989-758-209-7
AU - Vibert B.
AU - M. Le Bars J.
AU - Rosenberger C.
AU - Charrier C.
PY - 2017
SP - 403
EP - 410
DO - 10.5220/0006205704030410