Biometric Secret Path for Mobile User Authentication: A Preliminary Study

Michael Beton (1) , Vincent Marie (1) , Christophe Rosenberger (1)

1 Equipe SAFE - Laboratoire GREYC - UMR6072

The quality assessment of the acquired biometric raw data is very important as it deeply affects the performance of biometric systems and consequently their usability. Poor quality samples increase the enrolment failures, and decrease the system performance. In this paper, we present a new quality assessment metric of fingerprints. Its main orginality lies in the use of a no-reference image quality metric. The proposed quality metric combines two types of parameters through a weighted sum optimized by a genetic algorithm: 1) image quality criterion and 2) pattern-based quality criteria using the extracted minutiae on the fingerprint image. BOZORTH3 matching system and the FVC2002 DB3 fingerprint database are used to clarify the benefits of the presented quality metric.

Domaines: Vision par ordinateur et reconnaissance de formes [cs.CV]

Michael Beton, Vincent Marie, Christophe Rosenberger. Biometric Secret Path for Mobile User Authentication: A Preliminary Study. International Conference on Mobile Applications and Security Management (ICMASM), Jun 2013, Tunisia. pp.6. ⟨hal-00848326⟩