TY  - JOUR
ID  - SisLab3361
UR  - https://doi.org/10.1080/24751839.2017.1404712
A1  - Le, Hong Hai
A1  - Nguyen, Ngoc Hoa
A1  - Nguyen, Tri Thanh
Y1  - 2018/05/26/
N2  - 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.
PB  - Taylor & Francis
JF  - Journal of Information and Telecommunication
SN  - 2475-1839
TI  - Speeding up and enhancing a large-scale fingerprint identification system on GPU
SP  - 1
AV  - public
EP  - 16
ER  -