×

Fingerprint ridge allocation in direct gray-scale domain. (English) Zbl 0998.68140

Summary: Ridges and ravines are the main components constituting a fingerprint. Traditional Automatic Fingerprint Identification Systems (AFIS) are based on minutiae matching techniques. The minutiae for fingerprint identification are defined by ride termination and ridge bifurcation. Most AFIS perform ridge line following process to automatically detect minutiae based on binary or skeleton fingerprint image. For low-quality fingerprint images, the preprocessing stage of an AFIS produces redundant minutiae or even destroys real minutiae. The minutiae detection algorithms in direct gray-scale domain have been developed to overcome these problems. The first step of gray-scale minutiae detection algorithm is to determine ridge locations and then perform gray-scale ridge line following algorithm to extract minutiae. However, the existing gray-scale minutiae detection techniques can only work on partial fingerprint image due to the ignorance of image background. Moreover, the gray value variation inside a ridge also generates redundant ridge points. In this paper, we propose a novel method, based on gray-level histogram decomposition, to locate the ridge points in complete fingerprint images. By decomposing the gray-level histogram, redundant ridge points can be eliminated according to some statistical parameters. Experimental results demonstrate that the correct rate can be over 95% even applied to poor-quality fingerprint images.

MSC:

68T10 Pattern recognition, speech recognition
PDFBibTeX XMLCite
Full Text: DOI

References:

[1] Moayer, B.; Fu, K. S., A syntactic approach to fingerprint pattern recognition, Pattern Recognition, 7, 1-23 (1975) · Zbl 0318.68059
[2] Isenor, D. K.; Zaky, S. G., Fingerprint identification using graph matching, Pattern Recognition, 19, 2, 113-122 (1986)
[3] Ratha, N. K.; Karu, K.; Chen, S.; Jain, A. K., A real-time matching system for large fingerprint database, IEEE Trans. Pattern Anal. Mach. Intell., 18, 8, 799-813 (1996)
[4] D. Miao, D. Maltoni, Direct gray-scale minutiae detection in fingerprints, IEEE. Trans. Pattern Anal. Mach. Intell. 19 (1) 1997.; D. Miao, D. Maltoni, Direct gray-scale minutiae detection in fingerprints, IEEE. Trans. Pattern Anal. Mach. Intell. 19 (1) 1997.
[5] O’Gorman, L.; Nickerson, J. V., An approach to fingerprint filter design, Pattern Recognition, 22, 1, 29-38 (1989)
[6] Mehtre, B. M.; Chatterjee, B., Segmentation of fingerprint image — a composite method, Pattern Recognition, 22, 4, 381-385 (1989)
[7] Xiao, Q.; Raffat, H., Fingerprint image postprocessinga combined statistical and structural approach, Pattern Recognition, 24, 10, 985-992 (1991)
[8] Blue, J. L., Evaluation of pattern classifiers for fingerprint and OCR application, Pattern Recognition, 27, 4, 485-501 (1994)
[9] Fitz, A. P.; Green, R. J., Fingerprint classification using a hexagonal fast fourier transform, Pattern Recognition, 29, 10, 1587-1597 (1996)
[10] Zhuang, X.; Wang, T.; Zhang, P., A highly robust estimator through partially likelihood function modeling and its application in computer vision, IEEE Trans. Pattern Anal. Mach. Intell., 14, 1, 19-35 (1992)
[11] Carlotto, M. J., Histogram analysis using a scale-space approach, IEEE Trans. Pattern Anal. Mach. Intell., PAMI-9, 1, 121-129 (1987)
[12] Zhuang, X.; Huang, Y.; Palaniappan, K.; Zhao, Y., Gaussain mixture density modeling, decomposition, and applications, IEEE Trans. on Image Process, 5, 9, 1293-1302 (1996)
[13] C. I. Watson, C. L. Wilson, Fingerprint Database, National Institute of Standards and Technology, Special Database 4, FPDB, April, 1992.; C. I. Watson, C. L. Wilson, Fingerprint Database, National Institute of Standards and Technology, Special Database 4, FPDB, April, 1992.
[14] E. R. Henry, Classification and use of fingerprint. Routledge, London, 1900.; E. R. Henry, Classification and use of fingerprint. Routledge, London, 1900.
[15] Baruch, O., Line thinning by line following, Pattern Recognition Lett., 8, 4, 271-276 (1988)
This reference list is based on information provided by the publisher or from digital mathematics libraries. Its items are heuristically matched to zbMATH identifiers and may contain data conversion errors. In some cases that data have been complemented/enhanced by data from zbMATH Open. This attempts to reflect the references listed in the original paper as accurately as possible without claiming completeness or a perfect matching.