Abstract
As one kind of image having strong texture character, ridge distance is the important attribute of fingerprint image. It is important to estimate the ridge distance correctly for improving the performance of the automatic fingerprint identification system. The traditional Fourier transform spectral analysis method had the worse redundancy degree in estimating the ridge distance because it was based on the two-dimension discrete Fourier spectrum. The paper introduces the sampling theorem into the fingerprint image ridge distance estimation method, transforms the discrete spectrum into two-dimension continuous spectrum and obtains the ridge distance on the frequency field. The experimental results indicate that the ridge distance obtained from this method is more accurate and has improved the rate of accuracy of the automatic fingerprint identification system to a certain extent.
Supported by the National Natural Science Foundation of China under Grant No. 06403010, Shandong Province Science Foundation of China under Grant No.Z2004G05 and Anhui Province Education Department Science Foundation of China under Grant No.2005KJ089.
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References
Hong, L., Jain, A.K., Bolle, R.: Identity Authentication Using Fingerprints. In: Proceedings of FirstInternational Conference on Audio and Video-Based Biometric Person Authentication, Switzerland, pp. 103–110 (1997)
Yin, L., Ning, X.: Development and Application of Automatic Fingerprint Identification Technology. Journal of Nanjing University (Natural Science), 29–35 (2002)
Hong, L., Wan, Y., Jain, A.K.: Fingerprint Image Enhancement: Algorithm and Performance Evaluation. IEEE Trans. on Pattern Analysis and Machine Intelligence, 777–789 (1998)
Sherlock, D., Monro, D.M., Millard, K.: Fingerprint Enhancement by Directional Fourier Filter. In: IEEE Proc. Vis. Image Signal Processing, pp. 87–94 (1994)
Sherstinsky, A., Picard, R.W.: Restoration and Enhancement of Fingerprint Images Using M-Lattice: A Novel Non-Linear Dynamical System. In: Proc. 12th, ICPR-B, Jerusalem, pp. 195–200 (1994)
Yin, Y., Tian, J., Yang, X.: Ridge Distance Estimation in Fingerprint Images: Algorithm and Performance Evaluation. EURASIP Journal on Applied Signal Processing, 495–502 (2004)
Kovacs-Vajna, Z.M., Rovatti, R., Frazzoni, M.: Fingerprint Ridge Distance Computation Methodologies. Pattern Recognition, 69–80 (2000)
O’Gorman, L., Neckerson, J.V.: An Approach to Fingerprint Filter Design. Pattern Recognition, 29–38 (1989)
Lin, W.C., Dubes, R.C.: A Review of Ridge Counting in Dermatoglyphics. Pattern Recognition, 1–8 (1983)
Douglas Hung, D.C.: Enhancement Feature Purification of Fingerprint Images. Pattern Recognition, 1661–1671 (1993)
Maio, D., Maltoni, D.: Ridge-Line Density Estimation in Digital Images. In: Proceedings of 14th International Conference on Pattern Recognition, Brisbane, Australia, pp. 534–538 (1998)
Yin, Y., Wang, Y., Yu, F.: A Method Based on Region Level for Ridge Distance Estimation. Chinese Computer Science, 201–208 (2003)
Chen, Y., Yin, Y., Zhang, X.: A Method Based on Statistics Window for Ridge Distance Estimation. Journal of image and graphics, 266–270 (2003)
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Zhan, X., Sun, Z., Yin, Y., Chu, Y. (2005). A Method Based on the Continuous Spectrum Analysis for Fingerprint Image Ridge Distance Estimation. In: Wang, L., Jin, Y. (eds) Fuzzy Systems and Knowledge Discovery. FSKD 2005. Lecture Notes in Computer Science(), vol 3614. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11540007_27
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DOI: https://doi.org/10.1007/11540007_27
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-28331-7
Online ISBN: 978-3-540-31828-6
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