Comparative Study of Fingerprint Database Indexing Methods

Joannes Falade (1, 2) , Sandra Cremer (3) , Christophe Rosenberger (2)

1 IN groupe
2 Equipe SAFE - Laboratoire GREYC - UMR6072
3 IN groupe

Nowadays, there are large country-sized fingerprint databases for identification purposes, for border access controls and also for Visa issuance procedures around the world. Fingerprint indexing techniques aim to speed up the research process in automatic fingerprint identification systems. Therefore, several preselection, classification and indexing techniques have been proposed in the literature. However, the proposed systems have been evaluated with different experimental protocols, that makes it difficult to assess their performances. The main objective of this paper is to provide a comparative study of fingerprint indexing methods using a common experimental protocol. Four fingerprint indexing methods, using naive, cascade, matcher and Minutiae Cylinder Code (MCC) approaches are evaluated on FVC databases from the Fingerprint Verification Competition (FVC) using the Cumulative Matches Curve (CMC) and for the first time using also the computing time required. Our study shows that MCC gives the best compromise between identification accuracy and computation time.

Mots clés: Locality-sensitive Hashing; Biometrics; matching; indexing; fingerprint; minutiae; quality metrics; NFIQ2

Domaines: Cryptographie et sécurité [cs.CR]

Joannes Falade, Sandra Cremer, Christophe Rosenberger. Comparative Study of Fingerprint Database Indexing Methods. CyberWorlds conference, Oct 2019, Kyoto, Japan. ⟨hal-02387781⟩