Speeding up and enhancing a large-scale fingerprint identification system on GPU
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...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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Taylor & Francis Group
2018-04-01
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| Series: | Journal of Information and Telecommunication |
| Subjects: | |
| Online Access: | http://dx.doi.org/10.1080/24751839.2017.1404712 |
| Summary: | 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 on Graphics Processing Units 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 K40 tesla devices with standard data-sets prove that the proposed algorithm can be comparable with the state-of-the-art approach, and is suitable for a real-time identification application. |
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| ISSN: | 2475-1839 2475-1847 |