A complete fingerprint matching algorithm on GPU for a large scale identification system

Abstract

Fingerprints are most used biometrics features for identification. Although state-of-the-art algorithms are very accurate, but the need for processing speed for databases with millions fingerprints are very demanding. GPU devices are used widely in parallel computing tasks for their efficiency and low-cost. Most approaches make use of GPU for the filtering process in a multi-stage matching system. In this paper, we present a complete fingerprint matching algorithm on GPU. Our approach uses minutia cylinder-code (MCC) representation with a global consolidation stage and a careful design to make it suitable for the architecture of GPU. The result tested with GTX- 680 device shows that the proposed algorithm can perform 1.8 millions matches per second, making it applicable for real time identification systems with databases of millions fingerprints.