JOURNAL ARTICLE

Upper core point detection using improved ant colony optimization algorithm

Tsong-Liang HuangChe-Wei LiuChia-Cheng ChaoKing-Tan LeeTsong‐Yau HwangChi-Ming Chung

Year: 2008 Journal:   Journal of Discrete Mathematical Sciences and Cryptography Vol: 11 (3)Pages: 253-265   Publisher: Taylor & Francis

Abstract

Abstract 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. Keywords and phrases: Ant colony optimization algorithmfingerprint image processing

Keywords:
Minutiae Ant colony optimization algorithms Fingerprint (computing) Computer science Artificial intelligence Point (geometry) Pattern recognition (psychology) Algorithm Matching (statistics) Ant colony Fingerprint recognition Orientation (vector space) Singular point of a curve Mathematics

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Citation History

Topics

Biometric Identification and Security
Physical Sciences →  Computer Science →  Signal Processing
Vehicle License Plate Recognition
Physical Sciences →  Engineering →  Media Technology
Advanced Steganography and Watermarking Techniques
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition

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