Abstract
Singularity is the special feature of fingerprints for identification and classification. Since the performance of singularity extraction depends on the quality of fingerprint images, image enhancement is required to improve the performance. Image enhancement with various image filters might be more useful than a filter, but it is very difficult to find a set of appropriate filters. In this paper, we propose a method that uses the genetic algorithm to find those filters for superior performance of singularity extraction. The performance of the proposed method has been verified by the experiment with NIST DB 4. Moreover, the proposed method does not need any expert knowledge to find the type and order of filters for the target domain, it can be easily applied to other applications of image processing.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Ratha, N., Bolle, R.: Automatic Fingerprint Recognition Systems. Springer, New York (2004)
Jain, A.K., Hong, L., Bolle, R.: On-line fingerprint verification. IEEE Transactions on Pattern Analysis and Machine Intelligence 19(4), 302–314 (1997)
Bazen, A.M., Gerez, S.H.: Systematic methods for the computation of the directional fields and singular points of fingerprints. IEEE Transactions on Pattern Analysis and Machine Intelligence 24(7), 905–919 (2002)
Bazen, A.M., Gerez, S.H.: Segmentation of fingerprint images. In: Proc. ProRISC 2001 Workshop on Circuits, Systems and Signal Processing, Veldhoven, The Netherlands, pp. 276–280 (2001)
Hong, L., Wan, Y., Jain, A.: Fingerprint image enhancement: Algorithm and performance evaluation. IEEE Transactions on Pattern Analysis and Machine Intelligence 20(8), 777–789 (1998)
Yang, J., Liu, L., Jiang, T., Fan, Y.: A modified Gabor filter design method for fingerprint image enhancement. Pattern Recognition Letters 24, 1805–1817 (2003)
Greenberg, S., Aldadjem, M., Kogan, D.: Fingerprint image enhancement using filtering techniques. Real-Time Imaging 8, 227–236 (2002)
Zhu, E., Yin, J., Zhang, G.: Fingerprint enhancement using circular Gabor filter. In: International Conference on Image Analysis and Recognition, pp. 750–758 (2004)
Goldberg, D.: Genetic Algorithm in Search, Optimization and Machine Learning. Addison-Wesley, Reading (1989)
Schmitt, L.M.: Theory of genetic algorithms. Theoretical Computer Science 259, 1–61 (2001)
Cho, S.B.: Emotional image and musical information retrieval with interactive genetic algorithm. Proceedings of the IEEE 92(4), 702–711 (2004)
Harvey, N.R., Marshall, S.: The use of genetic algorithms in morphological filter design. Signal Processing: Image Communication 8, 55–71 (1996)
Yager, N., Admin, A.: Fingerprint classification: A review. Pattern Analysis and Application 7, 77–93 (2004)
Chong, M.M.S., Ngee, T.H., Jun, L., Gay, R.K.L.: Geometric framework for fingerprint image classification. Pattern Recognition 30, 1475–1488 (1997)
Zhang, Q., Yan, H.: Fingerprint classification based on extraction and analysis of singularities and pseudo ridges. Pattern Recognition 37, 2233–2243 (2004)
Jain, A.K., Prabhakar, S., Hong, L.: A multichannel approach to fingerprint classification. IEEE Transactions on Pattern Analysis and Machine Intelligence 21(4), 348–359 (1999)
Cappelli, R., Lumini, A., Maio, D., Maltoni, D.: Fingerprint classification by directional image partitioning. IEEE Transactions on Pattern Analysis and Machine Intelligence 21(5), 402–421 (1999)
Ross, A., Jain, A., Reisman, J.: A hybrid fingerprint matcher. Pattern Recognition 36, 1661–1673 (2003)
Gonzalez, R., Woods, R.: Digital Image Processing. Addison Wesley, Reading (1992)
Schmitt, L.M.: Theory of genetic algorithms II: Models for genetic operators over the string-tensor representation to populations and convergence to global optima for arbitrary fitness function under scaling. Theoretical Computer Science 310, 181–231 (2004)
Watson, C., Wilson, C.: NIST Special Database 4. Fingerprint Database. National Institute of Standard and Technology (1992)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2006 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Cho, UK., Hong, JH., Cho, SB. (2006). Evolutionary Singularity Filter Bank Optimization for Fingerprint Image Enhancement. In: Rothlauf, F., et al. Applications of Evolutionary Computing. EvoWorkshops 2006. Lecture Notes in Computer Science, vol 3907. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11732242_34
Download citation
DOI: https://doi.org/10.1007/11732242_34
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-33237-4
Online ISBN: 978-3-540-33238-1
eBook Packages: Computer ScienceComputer Science (R0)