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Reseach Article

Fingerprint Image Enhancement through Particle Swarm Optimization

by M. James Stephen, P. V. G. D. Prasad Reddy, V. Vasavi
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 66 - Number 21
Year of Publication: 2013
Authors: M. James Stephen, P. V. G. D. Prasad Reddy, V. Vasavi
10.5120/11243-6459

M. James Stephen, P. V. G. D. Prasad Reddy, V. Vasavi . Fingerprint Image Enhancement through Particle Swarm Optimization. International Journal of Computer Applications. 66, 21 ( March 2013), 34-40. DOI=10.5120/11243-6459

@article{ 10.5120/11243-6459,
author = { M. James Stephen, P. V. G. D. Prasad Reddy, V. Vasavi },
title = { Fingerprint Image Enhancement through Particle Swarm Optimization },
journal = { International Journal of Computer Applications },
issue_date = { March 2013 },
volume = { 66 },
number = { 21 },
month = { March },
year = { 2013 },
issn = { 0975-8887 },
pages = { 34-40 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume66/number21/11243-6459/ },
doi = { 10.5120/11243-6459 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T21:23:22.055381+05:30
%A M. James Stephen
%A P. V. G. D. Prasad Reddy
%A V. Vasavi
%T Fingerprint Image Enhancement through Particle Swarm Optimization
%J International Journal of Computer Applications
%@ 0975-8887
%V 66
%N 21
%P 34-40
%D 2013
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Fingerprint image enhancement is an essential preprocessing step to extract qualitative minutiae from a fingerprint image. The application of Particle Swarm Optimization (PSO), one of the well known soft computing techniques for fingerprint image enhancement is proposed in this paper. The fingerprint image enhancement algorithm, which is designed based on PSO, is implemented to improve the quality of the image and the clarity of ridges. The objective of the proposed PSO based enhancement method is to maximize an objective fitness criterion in order to enhance the contrast and minutiae detail in a fingerprint image. PSO does not require selection, crossover and mutation operations in comparison to GA. Both objective and subjective evaluations are performed on the resulted fingerprint images. NFIS2 of NIST is used to verify the improvement in the quality of the image. The results are compared with existing techniques like Contrast Limited Adaptive Histogram Equalization (CLAHE), Wiener filter, Median filter. Various experiments were carried out on the fingerprint data sets, which are collected from "CASIA-FingerprintV5" and FVC 2004 of MSU. The proposed PSO based fingerprint enhancement image outperforms many existing enhancement techniques.

References
  1. Eberhart R. C. Kennedy J. , A New Optimizer Using Particle Swarm Theory, Sixth International Symposium on Micro Machine and Human Science, Nagoya, Japan, 1995, pp. 39-43.
  2. Shi, Y. and Eberhart, R. C. (1998) A modified particle swarm optimizer,In Proc. IEEE International Conference on Evolutionary Computation. pp. 69–73.
  3. Apurba Gorai,Ashish Ghosh,"Gray-level Image Enhancement By Particle Swarm Optimization", 2009 World Congress on Nature & Biologically Inspired Computing (NaBIC 2009)
  4. Malik Braik, Alaa Sheta and Aladdin Ayesh,"Image Enhancement Using Particle Swarm Optimization", Proceedings of the World Congress on Engineering 2007 Vol I WCE 2007, July 2 - 4, 2007, London, U. K.
  5. R. C. Gonzales, R. E. Woods, Digital Image Processing. New York: Addison-Wesley, 1987
  6. F. Saitoh, "Image contrast enhancement using genetic algorithm," in Proc. IEEE SMC, Tokyo, Japan, pp. 899-904, 1993.
  7. J. Galbally, F. Alonso-Fernandez, J. Fierrez and J. Ortega-Garcia, "A High Performance Fingerprint Liveness Detection Method Based on Quality Related Features", Future Generation Computer Systems, Vol. 28, pp. 311-321, 2012.
  8. J. Galbally, J. Fierrez, F. Alonso-Fernandez and M. Martinez-Diaz, "Evaluation of Direct Attacks to Fingerprint Verification Systems", Telecommunication Systems, Special Issue on Biometrics, Vol. 47, n. 3, pp. 243-254, 2011.
  9. J. Galbally-Herrero, J. Fierrez-Aguilar, J. D. Rodriguez-Gonzalez, F. Alonso-Fernandez, J. Ortega-Garcia and M. Tapiador, "On the vulnerability of fingerprint verification systems to fake fingerprint attacks", in Proc. IEEE Intl. Carnahan Conf. on Security Technology, ICCST, pp. 130-136, Lexington, USA, October 2006.
  10. Tabassi, E. , & Wilson, C. L. (2005). A novel approach to fingerprint image quality. Proc. IEEE ICIP, 2, 37–40.
  11. Alonso-Fernandez, F. , Fierrez, J. , et al. (2003). A comparative study of fingerprint image quality estimation methods. IEEE Trans. on Information Forensics and Security, 2, 734–743.
  12. Watson, G. I. , Garris, M. D. , et al. (2004). User's guide to NIST fingerprint image software 2 (NFIS2). National Institute of Standards and Technology.
  13. Chaohong Wu, Zhixin Shi, and Venu Govindaraju. Fingerprint image enhancement method using directional median Filter, in biometric technology for human identi¯cation. In Proceedings of the SPIE, pages 250{256, 2004.
  14. Sharat Chikkerur, Alexander N. Cartwright, and Venu Govindaraju. K-plet and cbfs: A graph based Fingerprint representation and matching algorithm. ICB, January 2006. , (Fingerprint Image Enhancement Using STFT Analysis)
  15. Riccardo Poli,, An Analysis of Publications on Particle Swarm Optimisation Applications, Technical Report CSM-, ISSN: 1744-8050 May 2007, Revised November 2007
  16. M. James Stephen and P. V. G. D. Prasad Reddy, Enhancing Fingerprint Image through Ridge Orientation with Neural Network Approach and Ternarization for Effective Minutiae Extraction, International Journal of Machine Learning and Computing,Vol. 2, No. 4, August 2012, Pg. 397-401
  17. M. James Stephen, P. V. G. D. Prasad Reddy, et al. / Removal of False Minutiae with Fuzzy Rules from the Extracted Minutiae of Fingerprint Image, Advances in Intelligent and Soft Computing,Jan 2012, vol 132/2012, pp. 853-860, 2012.
  18. M. James Stephen, P. V. G. D Prasad Reddy, "Implementation of Easy Fingerprint Image Authentication with Traditional Euclidean and Singular Value Decomposition Algorithms", Int. J. Advance. Soft Comput. Appl. , Vol. 3, No. 2, July 2011, ISSN 2074-8523; Copyright © ICSRS Publication, 2011.
  19. D. Maio, D. Maltoni, R. Cappelli, J. L. Wayman and A. K. Jain, "FVC2004: Third Fingerprint Verification Competition", Proc. International Conference on Biometric Authentication (ICBA), pp. 1-7, Hong Kong, July 2004.
  20. M. James Stephen, P. V. G. D Prasad Reddy, "Easy Fingerprint Image Authentication with Traditional Euclidean distance" International Journal on Computer Engineering and Information Technology (IJCEIT), Volume No. 26, Isuue-1, PP [ 01-11]
  21. M. James Stephen, P. V. G. D Prasad Reddy, et. al " Fingerprint Image Enhancement with Neural Network and Effective Extraction of Minutiae" 2011 3rd International Conference on Machine Learning and Computing (ICMLC 2011), V4 301-306.
Index Terms

Computer Science
Information Sciences

Keywords

Fingerprint Image Enhancement Minutiae extraction PSO