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Consensus Fingerprint Matching with Genetically Optimised Approach

Sheng, Weiguo, Howells, Gareth, Fairhurst, Michael, Deravi, Farzin, Harmer, Karl (2009) Consensus Fingerprint Matching with Genetically Optimised Approach. Pattern Recognition, 42 (7). pp. 1399-1407. ISSN 0031-3203. (doi:10.1016/j.patcog.2008.11.038) (The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided) (KAR id:23132)

The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided.
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Fingerprint matching has been approached using various criteria based on different extracted features. However, robust and accurate fingerprint matching is still a challenging problem. In this paper, we propose an improved integrated method which operates by first suggesting a consensus matching function which combined different matching criteria based on heterogeneous features. We then devise a genetically guided approach to optimise the consensus matching function for simultaneous fingerprint alignment and verification. Since different features usually offer complementary information about the matching task, the consensus function is expected to improve the reliability of fingerprint matching. A related motivation for proposing such a function is to build a robust criterion that can perform well over a variety of different fingerprint matching instances. Additionally, by employing the global search functionality of a genetic algorithm along with a local matching operation for population initialisation, we aim to identify the optimal or near optimal global alignment between two fingerprints. The proposed algorithm is evaluated by means of a series of experiments conducted on public domain collections of fingerprint images and compared with previous work. Experimental results show that the consensus function can lead to a substantial improvement in performance while the local matching operation helps to identify promising initial alignment configurations, thereby speeding up the verification process. The resulting algorithm is more accurate than several other proposed methods which been implemented for comparison.

Item Type: Article
DOI/Identification number: 10.1016/j.patcog.2008.11.038
Uncontrolled keywords: Alignment, fingerprints, genetic algorithms (GAs), verification
Subjects: T Technology > TK Electrical engineering. Electronics. Nuclear engineering > TK7800 Electronics > TK7880 Applications of electronics > TK7882.B56 Biometric identification
Divisions: Divisions > Division of Computing, Engineering and Mathematical Sciences > School of Engineering and Digital Arts
Funders: Engineering and Physical Sciences Research Council (
Depositing User: J. Harries
Date Deposited: 27 Oct 2009 15:14 UTC
Last Modified: 12 Jul 2022 10:40 UTC
Resource URI: (The current URI for this page, for reference purposes)

University of Kent Author Information

Howells, Gareth.

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Fairhurst, Michael.

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Deravi, Farzin.

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