Online Fingerprint Verification Algorithm and Distributed System
Ping Zhang, Xi Guo, Jyotirmay Gadedadikar
.
DOI: 10.4236/jsip.2011.22011   PDF    HTML     7,709 Downloads   15,319 Views   Citations

Abstract

In this paper, a novel online fingerprint verification algorithm and distribution system is proposed. In the beginning, fingerprint acquisition, image preprocessing, and feature extraction are conducted on workstations. Then, the extracted feature is transmitted over the internet. Finally, fingerprint verification is processed on a server through web-based database query. For the fingerprint feature extraction, a template is imposed on the fingerprint image to calculate the type and direction of minutiae. A data structure of the feature set is designed in order to accurately match minutiae features between the testing fingerprint and the references in the database. An elastic structural feature matching algorithm is employed for feature verification. The proposed fingerprint matching algorithm is insensitive to fingerprint image distortion, scale, and rotation. Experimental results demonstrated that the matching algorithm is robust even on poor quality fingerprint images. Clients can remotely use ADO.NET on their workstations to verify the testing fingerprint and manipulate fingerprint feature database on the server through the internet. The proposed system performed well on benchmark fingerprint dataset.

Share and Cite:

P. Zhang, X. Guo and J. Gadedadikar, "Online Fingerprint Verification Algorithm and Distributed System," Journal of Signal and Information Processing, Vol. 2 No. 2, 2011, pp. 79-87. doi: 10.4236/jsip.2011.22011.

Conflicts of Interest

The authors declare no conflicts of interest.

References

[1] Z. Miklos and K. Vajna, “A Fingerprint Verification System Based on Triangular Matching and Dynamic Time Warping,” IEEE Transaction on Pattern Recognition and Machine Intelligence, Vol. 22, No. 11, November 2000, pp. 1266-1276. doi:10.1109/34.888711
[2] N. K. Ratha, K. Karu, S. Chen and A. K. Jain, “A Real-Time Matching System for Large Fingerprint Database,” IEEE Transaction on Pattern Analysis and Machine Intelligence, Vol. 18, No. 8, August 1996, pp. 799- 813. doi:10.1109/34.531800
[3] A. K. Jain, L. Hong and R. Bolle, “On-line Fingerprint Verification,” IEEE Transaction on Pattern Analysis and Machine Intelligence, Vol. 19, No. 4, April 1997, pp. 302-314. doi:10.1109/34.587996
[4] T. Y. Zhang and C. Y. Suen, “A Fast Parallel Algorithm for Thinning Digital Patterns,” Communication of the ACM, Vol. 27, No. 3, March 1984, pp. 236-239. doi:10.1145/357994.358023
[5] J. H. Wegstein, “An Automated Fingerprint Identification System,” Technical Report 500-89, National Bureau of Standards, Bethesda, 1982.
[6] S. Umeyama, “Parametterized Point Pattern Matching and its Application to Recognition of Object Families,” IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 15, No. 2, February 1993, pp. 136-144. doi:10.1109/34.192485
[7] D. K. Isenor and S. G. Zaky, “Fingerprint Identification Using Graph Matching,” Pattern Recognition, Vol. 19, No. 2, 1986, pp.113-122.
[8] N. Ansari, M. H. Chen and E. S. H. Hou, “A Genetic Algorithm for Point Pattern Mattering, Dynamic, Genetic, and Chaotic Programming,” John Wiley and Sons, New York, 1992, pp. 353-371.
[9] J. Ton and A. K. Jain, “Registering Landsat Images by Point Matching,” IEEE Transaction on Geoscience and Remote Sensing, Vol. 27, No. 5, September 1989, pp. 642-651. doi:10.1109/TGRS.1989.35948
[10] V. S. Srinivasan and N. N. Murthy, “Detection of Singular Points in Fingerprint Images,” Pattern Recognition, Vol. 25, No. 2, February 1992, pp. 139-153. doi:10.1016/0031-3203(92)90096-2
[11] A. K. Hrechak and J. A. Mchugh, “Automated Fingerprint Recognition Using Structural Matching,” Pattern Recognition, Vol. 23, No. 8, 1990, pp. 893-904. doi:10.1016/0031-3203(90)90134-7
[12] A. K. Jain, S. Prabhakar and S. Pankanti, “Filterbank-Based Fingerprint Matching,” IEEE Transactions on Image Processing, Vol. 9, No. 5, 2000, pp. 846-859. doi:10.1109/83.841531
[13] P. M. Patil, R. S. Suralkar and H. K. Abhyankar, “Fingerprint Verification Based on Fixed Length Square Finer Code,” Proceeding of IEEE Conference on Tools with Artificial Intelligence, Hong Kong, 16 November 2005, pp. 657-662.
[14] K. Huang and S. Aviyente, “Choosing Best Basis in Wavelet Packets for Fingerprint Matching,” Proceedings of IEEE Conference on Image Processing, East Lansing, 24-27 October 2004, pp. 1249-1252.
[15] N. Y. Khan and M. Y. Javed, “Efficient Fingerprint Matching Technique Using Wavelet Based Features,” Proceedings of Digital Image Computing Techniques and Applications, 2007, pp. 253-259.
[16] X. Tan and B. Bhanu, “Fingerprint Verification Using Genetic Algorithm,” Proceedings of 6th IEEE Workshop on Applications of Computer Vision, 2002, pp. 79-83.
[17] J. Gu, J. Zhou and X. Tang, “Fingerprint Recognition by Combining Global Structure and Local Cues,” IEEE Transactions on Image Processing, Vol. 15, No. 7, 2006, pp. 1951-1964.
[18] A. Ross, S. C. Dass and A. K. Jain, “Fingerprint Warping Using Ridge Curve Correspondences,” IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 28, No. 1, 2006, pp. 19-30. doi:10.1109/TPAMI.2006.11
[19] C. J. Watson and C. L. Wilson, “NIST Special Database 4 Fingerprint Database,” National Institute of Standards and Technology Advanced Systems Division Image Recognition Group, 17 March 1992.
[20] R. C. Gonzalez and R. E. Woods, “Digital Image Processing,” 3rd Version, Pearson Prentice Hall, 2008.

Copyright © 2024 by authors and Scientific Research Publishing Inc.

Creative Commons License

This work and the related PDF file are licensed under a Creative Commons Attribution 4.0 International License.