Sheng, Weiguo, Howells, Gareth, Fairhurst, Michael, Deravi, Farzin (2007) A memetic fingerprint matching algorithm. IEEE Transactions on Information Forensics and Security, 2 (3). pp. 402-412. ISSN 1556-6013. (doi:10.1109/TIFS.2007.902681) (KAR id:2068)
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Official URL: http://dx.doi.org/10.1109/TIFS.2007.902681 |
Abstract
Minutiae point pattern matching is the most common approach for fingerprint verification. Although many minutiae point pattern matching algorithms have been proposed, reliable automatic fingerprint verification remains as a challenging problem, both with respect to recovering the optimal alignment and the construction of an adequate matching function. In this paper, we develop a memetic fingerprint matching algorithm (MFMA) which aims to identify the optimal or near optimal global matching, between two minutiae sets. Within the MFMA, we first introduce an efficient matching operation to produce an initial population of local alignment configurations by examining local features of minutiae. Then, we devise a hybrid evolutionary procedure by combining the use of the global search functionality of a genetic algorithm with a local improvement operator to search for the optimal or near optimal global alignment. Finally, we define a reliable matching function for fitness computation. The proposed algorithm was evaluated by means of a series of experiments conducted on the FVC2002 database and compared with previous work. Experimental results confirm that the MFMA is an effective and practical matching algorithm for fingerprint verification. The algorithm is faster and more accurate than a traditional genetic-algorithm-based method. It is also more accurate than a number of other methods implemented for comparison, though our method generally requires more computational time in performing fingerprint matching.
Item Type: | Article |
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DOI/Identification number: | 10.1109/TIFS.2007.902681 |
Uncontrolled keywords: | alignment; fingerprints; genetic algorithms (GAs); matching; memetic algorithms; minutiae |
Subjects: |
T Technology > TK Electrical engineering. Electronics. Nuclear engineering Q Science > QA Mathematics (inc Computing science) > QA 75 Electronic computers. Computer science |
Divisions: | Divisions > Division of Computing, Engineering and Mathematical Sciences > School of Engineering and Digital Arts |
Depositing User: | Stephen Holland |
Date Deposited: | 19 Dec 2007 19:26 UTC |
Last Modified: | 05 Nov 2024 09:32 UTC |
Resource URI: | https://kar.kent.ac.uk/id/eprint/2068 (The current URI for this page, for reference purposes) |
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