Upper core point detection using improved ant colony optimization algorithm

Minutiae detection is a crucial process in an automatic fingerprint identification system. Most fingerprint comparison algorithms are based on minutiae matching. However, the local orientation changes very rapidly in the singular point area. It is difficult to locate the singular point precisely. Th...

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Published inJournal of discrete mathematical sciences & cryptography Vol. 11; no. 3; pp. 253 - 265
Main Authors Huang, Tsong-Liang, Liu, Che-Wei, Chao, Chia-Cheng, Lee, King-Tan, Hwang, Tsong-Yau, Chung, Chi-Ming
Format Journal Article
LanguageEnglish
Published Taylor & Francis Group 01.06.2008
Subjects
Ant colony optimization algorithm
fingerprint image processing
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Summary:Minutiae detection is a crucial process in an automatic fingerprint identification system. Most fingerprint comparison algorithms are based on minutiae matching. However, the local orientation changes very rapidly in the singular point area. It is difficult to locate the singular point precisely. The Ant Colony Optimization Algorithm (ACOA) is extensively used in multi-objective and optimal problems. But the ACOA is still not used in fingerprint image processing. In this paper, we suggest an improved Ant Colony Optimization Algorithm to extract the upper core point of fingerprints. Finally, the proposed algorithms are tested with some fingerprint images and show significant improvement in the experiments.
Bibliography:ObjectType-Article-2
SourceType-Scholarly Journals-1
ObjectType-Feature-1
content type line 23
ISSN:0972-0529
2169-0065
DOI:10.1080/09720529.2008.10698182