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Reseach Article

A New Hybrid Technique for Iris Recognition

by Sarabjeet Kaur, Ada
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 122 - Number 13
Year of Publication: 2015
Authors: Sarabjeet Kaur, Ada
10.5120/21759-4993

Sarabjeet Kaur, Ada . A New Hybrid Technique for Iris Recognition. International Journal of Computer Applications. 122, 13 ( July 2015), 11-18. DOI=10.5120/21759-4993

@article{ 10.5120/21759-4993,
author = { Sarabjeet Kaur, Ada },
title = { A New Hybrid Technique for Iris Recognition },
journal = { International Journal of Computer Applications },
issue_date = { July 2015 },
volume = { 122 },
number = { 13 },
month = { July },
year = { 2015 },
issn = { 0975-8887 },
pages = { 11-18 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume122/number13/21759-4993/ },
doi = { 10.5120/21759-4993 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T23:10:27.795312+05:30
%A Sarabjeet Kaur
%A Ada
%T A New Hybrid Technique for Iris Recognition
%J International Journal of Computer Applications
%@ 0975-8887
%V 122
%N 13
%P 11-18
%D 2015
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Iris recognition is considered as the most accurate biometric method. In this paper, we have developed a system that can recognize human iris patterns and an analysis of the results is done. A novel mechanism has been used for implementation of the system. Feature encoding has been used to extract the most discriminating features of the iris and is done using SIFT scheme. And finally the biometric templates are classified using SVM and Neural Network which tells us whether the two iris images are same or not and on the basis of that performance metric are evaluated Accuracy, precision and false positive rate using MATLAB environment.

References
  1. L. Flom and A. Safir, "Iris recognition system," U. S. Patent 4641349, Feb. 3, 1987.
  2. J. G. Daugman, "High confidence visual recognition of persons by a test of statistical independence," IEEE Trans. Pattern Anal. Mach. Intell. , vol. 15, no. 11, pp. 1148–1161,Nov. 1993.
  3. P. Wildes, "Iris recognition: An emerging biometric technology," Proc. IEEE, vol. 85,no. 9, pp. 1348–1363,Sep. 1997.
  4. W. W. Boles and B. Boashash, "A human identification technique using images of the iris and wavelet transform," IEEE Trans. Signal Process. , vol. 46,no4,pp. 1185–1188,Apr. 1998. .
  5. L. Ma, T. Tan, Y. Wang, and D. Zhang, "Personal identification based on iris texture analysis," IEEE Trans. Pattern Anal. Mach. Intell. , vol. 25,no. 12, pp. 1519–1533,Dec. 2003. .
  6. Z. Sun, T. Tan, and Y. Wang, "Robust encoding of local ordinal measures: A general framework of iris recognition," in Proc. ECCV WorkshopBioAW, 2004, pp. 270–282.
  7. C. Sanchez-Avila and R. Sanchez-Reillo, "Two different approaches for iris recognition using Gabor filters and multiscalezerocrossingrepresentation,"PatternRecognit. ,vol. 38,no. 2,pp. 231–240,Feb. 2005.
  8. K. Miyazawa, K. Ito, T. Aoki, K. Kobayashi, and H. Nakajima, "An effective approach for iris recognition using phase-based image matching,"IEEE Trans. Pattern Anal. Mach. Intell. , vol. 30, no. 10, pp. 1741–1756,Oct. 2008.
  9. L. Birgale and M. Kokare, "Iris recognition without iris normalization,"J. Comput. Sci. ,vol. 6,no. 9,pp. 1042-1047,2010.
  10. C. Belcher and Y. Du, "Region-based SIFT approach to iris recognition,"Opt. LasersEng. ,vol. 47,no. 1,pp. 139-147,Jan. 2009
  11. L. Birgale and M. Kokare, "Iris recognition without iris normalization,"J. Comput. Sci. , vol. 6, no. 9, pp. 1042–1047, 2010.
  12. S. Shah and A. Ross, "Iris segmentation using geodesic active contours,"IEEE Trans. Inf. Forensics Security, vol. 4, no. 4, pp. 824–836, Dec. 2009.
  13. K. Roy, P. Bhattacharya, and C. Y. Suen, "Towards nonideal iris recognition based on level set method, genetic algorithms and adaptive asymmetrical SVMs," Eng. Appl. Artif. Intell. , vol. 24, no. 3, pp. 458–475,Apr. 2011
  14. C. Belcher and Y. Du, "Region-based SIFT approach to iris recognition," Opt. Lasers Eng. , vol. 47, no. 1, pp. 139–147, Jan. 2009.
  15. Wildes, R. P "Iris recognition: an emerging biometric technology" Proceeding of IEEE, Vol-9, pp. 1348-1364, 1997.
Index Terms

Computer Science
Information Sciences

Keywords

SIFT (Scale invariant feature transform) Iris authentication Support Vector Machine (SVM) Neural network (NN) Hough circle transform (HCT) least mean square(LMS)