Optimization of Fingerprint Recognition using Genetic Algorithm
dc.contributor.author | Nwoye, E. O. | |
dc.contributor.author | Oronti, I. B. | |
dc.contributor.author | Chukwuma, V. M. | |
dc.contributor.author | Nwaneri, S. C. | |
dc.date.accessioned | 2019-09-20T15:08:53Z | |
dc.date.available | 2019-09-20T15:08:53Z | |
dc.date.issued | 2012-06-01 | |
dc.description.abstract | Fingerprint as a biometric identifier is one of the most reliable personal identification tools and enjoys widespread applications. In this research the Genetic Algorithm GA is used to ooptimize the alignment and matching methods in the recognition process. After the pre-processing, post processing and feature extraction, the alignment algorithm is used to first align the minutiae points and then a pair of minutiae is matched if the distance and the rotational angle between them is equal to or less than a predefine value. The GA as a search method is employed to locate optimal values of these minutiae distance s and angles and match them as applicable. The GA was then applied to the Fingerprint Verification Competition 2002 (FVC2002). Database 1 with a good performance and very high recognition rate with an attendant penalty of longer computation time which can be improved by using a faster processor. The method also performed better than all of the commonly used algorithms listed in terms of Equal Error Rate EER | en_US |
dc.identifier.issn | 0795-2333 | |
dc.identifier.uri | https://ir.unilag.edu.ng/handle/123456789/5901 | |
dc.language.iso | en | en_US |
dc.publisher | Journal of Engineering Research | en_US |
dc.relation.ispartofseries | Vol. 17;02 | |
dc.subject | Fingerprint recognition | en_US |
dc.subject | Genetic Algorithm | en_US |
dc.subject | Minutiae Matching | en_US |
dc.subject | Fingerprint Image Enhancement | en_US |
dc.subject | Minutiae detection | en_US |
dc.title | Optimization of Fingerprint Recognition using Genetic Algorithm | en_US |
dc.type | Article | en_US |
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