Fingerprint Class Recognition For Securing EMV Transaction

Benoît Vibert (1) , Jean-Marie Le Bars (1) , Christophe Charrier (1) , Christophe Rosenberger (1)

1 Equipe SAFE - Laboratoire GREYC - UMR6072

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.

Mots clés: EMV; Biometric; ISO template; Fingerprint class recognition; Transaction security

Domaines: Informatique [cs]; Traitement du signal et de l'image [eess.SP]; Cryptographie et sécurité [cs.CR]

Benoît Vibert, Jean-Marie Le Bars, Christophe Charrier, Christophe Rosenberger. Fingerprint Class Recognition For Securing EMV Transaction. International Conference on Information Systems Security and Privacy, Feb 2017, Porto, Portugal. ⟨hal-01444422⟩