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Detecting fingerprint minutiae by run length encoding scheme. (English) Zbl 1096.68727

Summary: Many approaches to minutiae extraction have already been proposed for automatic fingerprint matching, and most transform fingerprint images into binary images through state-of-the-art algorithms and submit the binary image to a thinning process. However, this paper proposes an original technique for extracting minutiae based on representing the ridge structure of a fingerprint image as a Run Length Code (RLC). The essential idea is to detect minutiae by searching for the termination points or bifurcation points of ridges in the RLC, rather than in a fingerprint image. Experimental results and a comparative analysis show that the proposed method is fairly reliable and faster than a conventional thinning-based method.

MSC:

68T10 Pattern recognition, speech recognition
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[1] L. Dale, Schools learn about the benefits of biometrics, in: M. Kockie (Ed.), Biometric Technology Today, vol. 9(6), Elsevier Science, Amsterdam, 2001, pp. 7-8.; L. Dale, Schools learn about the benefits of biometrics, in: M. Kockie (Ed.), Biometric Technology Today, vol. 9(6), Elsevier Science, Amsterdam, 2001, pp. 7-8.
[2] Maio, D.; Maltoni, D., Direct gray-scale minutiae detection in fingerprint, IEEE Transactions on Pattern Analysis and Machine Intelligence, 19, 1, 27-40 (1997)
[3] Lee, H. C.; Gaensslen, R. E., Advances in Fingerprint Technology (2001), CRC Press: CRC Press Boca Raton
[4] Bolle, R. M.; Senior, A. W.; Ratha, N. K.; Pankanti, S., Fingerprint minutiae: a constructive definition, (Tistarelli, M.; Bigün, J.; Jain, A. K., Lecture Notes in Computer Science 2338 (2002), Springer-Verlag: Springer-Verlag New York), 58-66 · Zbl 1046.68682
[5] W.F. Leung, S.H. Leung, W.H. Lau, A. Luk, Fingerprint recognition using neural network, in: Proceedings of the 1991 IEEE Workshops on Neural Networks for Signal Processing, 1991, pp. 226-235.; W.F. Leung, S.H. Leung, W.H. Lau, A. Luk, Fingerprint recognition using neural network, in: Proceedings of the 1991 IEEE Workshops on Neural Networks for Signal Processing, 1991, pp. 226-235.
[6] D.M. Weber, A cost effective fingerprint verification algorithm for commercial applications, in: Proceedings of the 1992 South African Symposium on Communications and Signal Processing, 1992, pp. 99-104.; D.M. Weber, A cost effective fingerprint verification algorithm for commercial applications, in: Proceedings of the 1992 South African Symposium on Communications and Signal Processing, 1992, pp. 99-104.
[7] Ratha, N. K.; Chen, S.; Jain, A. K., Adaptive flow orientation-based feature extraction in fingerprint images, Pattern Recognition, 28, 11, 1657-1672 (1995)
[8] B. Bhanu, X. Tan, Learned templates for feature extraction in fingerprint images, in: Proceedings of the 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, vol. II, 2001, pp. 591-596.; B. Bhanu, X. Tan, Learned templates for feature extraction in fingerprint images, in: Proceedings of the 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, vol. II, 2001, pp. 591-596.
[9] Farina, A.; Kovács-Vajna, Z. M.; Leone, A., Fingerprint minutiae extraction from skeletonized binary image, Pattern Recognition, 32, 5, 877-889 (1999)
[10] Wilson, C. L.; Candela, G. T.; Watson, C. I., Neural-network fingerprint classification, Journal of Artificial Neural Networks, 1, 2, 203-228 (1994)
[11] Karu, K.; Jain, A. K., Fingerprint classification, Pattern Recognition, 29, 3, 389-404 (1996)
[12] Mehtre, B. M.; Chatterjee, B., Segmentation of fingerprint images—a composite method, Pattern Recognition, 22, 4, 381-385 (1989)
[13] Jain, A. K.; Farrokhnia, F., Unsupervised texture segmentation using Gabor filters, Pattern Recognition, 24, 12, 1167-1186 (1991)
[14] Kawagoe, M.; Tojo, A., Fingerprint pattern classification, Pattern Recognition, 17, 3, 295-303 (1984)
[15] Rao, A. R., A Taxonomy for Texture Description and Identification (1990), Springer-Verlag: Springer-Verlag New York · Zbl 0743.68136
[16] Hong, L.; Wan, Y.; Jain, A. K., Fingerprint image enhancement: algorithm and performance evaluation, IEEE Transactions on Pattern Analysis and Machine Intelligence, 20, 8, 777-789 (1998)
[17] Otsu, N., A threshold selection method from gray-level histograms, IEEE Transactions on Systems, Man, and Cybernetics, 9, 1, 62-66 (1979)
[18] Shapiro, L. G.; Stockman, G. C., Computer Vision (2001), Prentice-Hall: Prentice-Hall Englewood Cliffs, NJ
[19] Zenzo, S. D.; Cinque, L.; Levialdi, S., Run-based algorithms for binary image analysis and processing, IEEE Transactions on Pattern Analysis and Machine Intelligence, 18, 1, 83-89 (1996)
[20] Govindan, V. K.; Shivaprasad, A. P., A pattern adaptive thinning algorithm, Pattern Recognition, 20, 6, 623-637 (1987)
[21] A.P. Fitz, R.J. Green, Fingerprint pre-processing on a hexagonal grid, in: Proceedings of the 1995 European Convention on Security and Detection, Brighton, UK, May 1995, pp. 257-260.; A.P. Fitz, R.J. Green, Fingerprint pre-processing on a hexagonal grid, in: Proceedings of the 1995 European Convention on Security and Detection, Brighton, UK, May 1995, pp. 257-260.
[22] Lam, L.; Lee, S. W.; Suen, C. Y., Thinning methodologies—a comprehensive survey, IEEE Transactions on Pattern Analysis and Machine Intelligence, 14, 9, 869-885 (1992)
[23] Wu, R. Y.; Tsai, W. H., A new one-pass parallel thinning algorithm for binary images, Pattern Recognition Letters, 13, 10, 715-723 (1992)
[24] Chen, Y. S.; Hsu, W. H., A modified fast parallel algorithm for thinning digital patterns, Pattern Recognition Letters, 7, 2, 99-106 (1988)
[25] Zhang, T. Y.; Suen, C. Y., A fast parallel algorithm for thinning digital patterns, Journal of Communications of the ACM, 27, 3, 236-240 (1984)
[26] Jain, A. K.; Hong, L.; Bolle, R., On-line fingerprint verification, IEEE Transactions on Pattern Analysis and Machine Intelligence, 19, 4, 302-314 (1997)
[27] Jain, L. C.; Halici, U.; Hayashi, I.; Lee, S. B.; Tsutsui, S., Intelligent Biometric Techniques in Fingerprint and Face Recognition (1999), CRC Press: CRC Press Boca Raton
[28] Xiao, Q.; Raafat, H., Fingerprint image postprocessing: a combined statistical and structural approach, Pattern Recognition, 24, 10, 985-992 (1991)
[29] Espinosa-Duró, V., Fingerprint thinning algorithm, IEEE Aerospace and Electronic Systems Magazine, 18, 9, 28-30 (2003)
[30] V. Espinosa-Duró, Mathematical morphology approaches for fingerprints thinning, Proceedings of the 36th Annual International Carnahan Conference on Security Technology, October 2002, pp. 43-45, 2002.; V. Espinosa-Duró, Mathematical morphology approaches for fingerprints thinning, Proceedings of the 36th Annual International Carnahan Conference on Security Technology, October 2002, pp. 43-45, 2002.
[31] Kim, S. J.; Lee, D. J.; Kim, J. H., Algorithm for detection and elimination of false minutiae in fingerprint images, (Bigun, J.; Smeraldi, F., Lecture Notes in Computer Science 2091 (2001), Springer-Verlag: Springer-Verlag New York), 235-240 · Zbl 0980.68570
[32] C.I. Watson, C.L. Wilson, NIST Special Database 4, Fingerprint Database, National Institute of Standard and Technology, 1992.; C.I. Watson, C.L. Wilson, NIST Special Database 4, Fingerprint Database, National Institute of Standard and Technology, 1992.
[33] Almansa, A.; Lindeberg, T., Fingerprint enhancement by shape adaptation of scale-space operators with automatic scale selection, IEEE Transactions on Image Processing, 9, 12, 2027-2042 (2000) · Zbl 0962.94018
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