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Huang, Tsong-Liang; Liu, Che-Wei; Chao, Chia Cheng; Lee, King-Tan; Hwang, Tsong-Yau; Chung, Chi-Ming

Upper core point detection using improved ant colony optimization algorithm. (English) Zbl 1183.94009

J. Discrete Math. Sci. Cryptography 11, No. 3, 253-265 (2008).
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.

MSC:

94A08 Image processing (compression, reconstruction, etc.) in information and communication theory
90C59 Approximation methods and heuristics in mathematical programming
68U10 Computing methodologies for image processing

Keywords:

improved ant colony optimization algorithm; upper core point of fingerprints; minutiae detection; fingerprint image processing
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