Exploiting GPU for large scale fingerprint identification

Abstract

Fingerprints are the most used biometrics features for identification. Although state-of-the-art algorithms are very accurate, but the need for fast processing speed for databases containing millions fingerprints is highly demanding. GPU devices are widely used in parallel computing tasks for its efficiency and low-cost. In this paper, we propose to adapt minutia cylinder-code (MCC) matching algorithm, an efficient algorithm in term of accuracy to GPU. The proposed method fits well with the architecture of the GPU that makes it easy to implement. The results of our experiments with a GTX- 680 device show that the proposed algorithm can perform 8.5 millions matches in a second that is suitable for real time identification systems having databases containing millions of fingerprints.