%0 Journal Article
%@ 2475-1839
%A Le, Hong Hai
%A Nguyen, Ngoc Hoa
%A Nguyen, Tri Thanh
%D 2018
%F SisLab:3361
%I Taylor & Francis
%J Journal of Information and Telecommunication
%P 1-16
%T Speeding up and enhancing a large-scale fingerprint identification system on GPU
%U https://eprints.uet.vnu.edu.vn/eprints/id/eprint/3361/
%X Fingerprint identification is one of the most common biometric feature problems which is used in many applications. Although state-of-the-art algorithms are very accurate, the need for fast processing a big database of millions of fingerprints is highly demanding. In this paper, we propose to adapt the fingerprint matching algorithm based on minutia cylinder-code (MCC) on Graphics Processing Units (GPUs) to speed up the matching. Another contribution of this paper is to add a consolidation stage after matching to enhance the precision. The experimental results on a GTX-680 and a K40 tesla devices with standard datasets prove the proposed algorithm can be comparable with the state-of-the-art approach, and suitable for a real time identification application.