Upper core point detection using improved ant colony optimization algorithm. (English) Zbl 1183.94009
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 processingReferences:
[1] | Lee H. C., Advances in Fingerprint Technology (1991) |
[2] | The science of fingerprints: classification and uses (1984) |
[3] | O’Gorman L., Biometrics: Personal Identification in a Networked Society (1999) |
[4] | Jain A. K., IEEE Trans. Pattern Anal. Machine Intell. 21 (4) pp 348– (1999) · doi:10.1109/34.761265 |
[5] | Jain A. K., Proc. IEEE Computer Society Conf. Computer Vision and Pattern Recognition (CVPR) 2 pp 187– (1999) |
[6] | Jain A. K., IEEE Trans. Image Processing 9 (5) pp 846– (2000) · doi:10.1109/83.841531 |
[7] | Srinivasan V. S., Pattern Recognition 25 (2) pp 139– (1992) · doi:10.1016/0031-3203(92)90096-2 |
[8] | Boer J., Proc. ProRISC2001 Workshop on Circuits, Systems and Signal Processing (2001) |
[9] | Stock, R. M. and Swonger, C. W. 1969.Development and evaluation of a reader of fingerprint minutiae, Cornell Aeronautical Laboratory, Technical Report CAL 13–17. No.XM-2478-X-1 |
[10] | Lee, S. H., Chang, S. H., Cheng, F. H. and Hsu, W. H. Fingerprint classification using singular points. IPPR Conference on CVGIP. pp.311–316. |
[11] | Dorigo M., Technical Report No. 91–016 Revised (1991) |
[12] | Dorigo M., IEEE Transactions on Systems, Man and Cybernetics–Part B 26 (1) pp 29– (1996) · doi:10.1109/3477.484436 |
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