Speeding up and enhancing a large-scale fingerprint identification system on GPU
| Autor: | Hong Hai Le, Ngoc Hoa Nguyen, Tri-Thanh Nguyen |
|---|---|
| Rok vydání: | 2017 |
| Předmět: |
parallel processing
Biometrics Matching (graph theory) Scale (ratio) Computer Networks and Communications Computer science Data_MISCELLANEOUS GPU 0211 other engineering and technologies 02 engineering and technology lcsh:Telecommunication Fingerprint identification Minutia cylinder code lcsh:TK5101-6720 0202 electrical engineering electronic engineering information engineering Computer Science (miscellaneous) Electrical and Electronic Engineering minutiae Minutiae 021110 strategic defence & security studies Minutia Cylinder-Code lcsh:T58.5-58.64 lcsh:Information technology business.industry matching Process (computing) Pattern recognition Computer Science Applications Parallel processing (DSP implementation) Feature (computer vision) 020201 artificial intelligence & image processing Artificial intelligence business |
| Zdroj: | Journal of Information and Telecommunication, Vol 2, Iss 2, Pp 147-162 (2018) |
| ISSN: | 2475-1847 2475-1839 |
| DOI: | 10.1080/24751839.2017.1404712 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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