CFP last date
20 January 2025
Call for Paper
February Edition
IJCA solicits high quality original research papers for the upcoming February edition of the journal. The last date of research paper submission is 20 January 2025

Submit your paper
Know more
The week's pick
Responsive image
SFLA-Based Line Balancing and Task Optimization in Master-Slave Controlled Hanger Transportation Systems for Garment Production

Duc Hoang Nguyen
Random Articles
Reseach Article

A Selective Feature Matching Approach for Iris Recognition

by Sambita Dalal, Tapasmini Sahoo
journal cover thumbnail

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 41 - Number 20
Year of Publication: 2012
Authors: Sambita Dalal, Tapasmini Sahoo
10.5120/5811-8102

Sambita Dalal, Tapasmini Sahoo . A Selective Feature Matching Approach for Iris Recognition. International Journal of Computer Applications. 41, 20 ( March 2012), 34-39. DOI=10.5120/5811-8102

@article{ 10.5120/5811-8102,
author = { Sambita Dalal, Tapasmini Sahoo },
title = { A Selective Feature Matching Approach for Iris Recognition },
journal = { International Journal of Computer Applications },
issue_date = { March 2012 },
volume = { 41 },
number = { 20 },
month = { March },
year = { 2012 },
issn = { 0975-8887 },
pages = { 34-39 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume41/number20/5811-8102/ },
doi = { 10.5120/5811-8102 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:30:08.114172+05:30
%A Sambita Dalal
%A Tapasmini Sahoo
%T A Selective Feature Matching Approach for Iris Recognition
%J International Journal of Computer Applications
%@ 0975-8887
%V 41
%N 20
%P 34-39
%D 2012
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Reliable automatic recognition of persons has long been an attractive goal of many researchers. Thus the recognition of an individual based on iris pattern is gaining more popularity due to the uniqueness of the pattern among the people which are highly stable starting from about one year past the date of birth, until death. The probability for the existence of two irises that are same has been theoretically estimated to be very high, i. e. one in 1072 which counts for the unique characterization of the iris. Although many approaches for iris recognition have been proposed by many researchers in the last few years, in this paper a selective iris feature matching method for iris recognition based on optimized wavelet decomposition of normalized iris image has been proposed. Comparing the average normalised correlation of the wavelet coefficients of optimised level and its adjacent levels improved matching is obtained, thus performing uniqueness verification of a person.

References
  1. Bowyer, K. W. , Hollingsworth, K. , Flynn, P. , " Image understanding for iris biometrics: a survey", Comp. Vision and Image Understanding 110 (2008) , pp: 281–307.
  2. Dobes, M. , Machala, L. , Tichavsky, P. , Pospisil, J. , "Human eye iris recognition using the mutual information", International Journal for Light and Electron Optics, No. 9, 2004, pp: 399-404.
  3. Flom, L. , Safir, A. , "Iris recognition system", US Patent no. 4 641 394, 1987.
  4. Daugman, J. , "The importance of being random: Statistical principles of iris recognition", Pattern Recognition, Vol. 36, No. 2, 2003, pp: 279-291.
  5. Daugman, J. , "High Confidence Visual Recognition of Persons by a Test of Statistical Independence", IEEE Trans. On Pattern Analysis and Machine Intelligence, Vol. 15, No. 11, 1993, pp: 1148-1161.
  6. Daugman, J. , "How iris recognition works", Proceedings of 2002 International Conference on Image Processing, Vol. 1, 2002.
  7. Wildes, R. , "Iris recognition: an emerging biometric technology", Proc. IEEE, 1997, 85(9), pp: 1348–1363.
  8. Yu, Li. , "Iris Verification Based on Fractional Fourier Transform", Proceedings of the International Conference on Machine Learning and Cybernetics, Beijing, Nov 2002, pp: 1470-1473.
  9. Tisse, C. L. , Torres L. , and Robert M. , "Person Identification based on iris patterns", Proceedings of the 15th International Conference on Vision interface, 2002.
  10. Zhu, Y. , Tan T. , and Yusag, "Biometric Personal Identification based on Iris Patterns", Pattern recognition, 15th Internal Configuration, vol. 2, 2004, pp: 801-804.
  11. Ma, Li. , Tan, Tieniu. , "Personal Identification Based on iris Texture Analysis'', IEEE Transaction on pattern analysis and machine intelligence, Vol. 25, No. 12, 2003, pp: 519-1533.
  12. Wibowo, Eric Prasetyo. , Maulana, Wisnu Sukma. , IEEE International Conference on Signal Processing, 2009, pp: 98-102.
  13. Wheeler, F M. , Perera, A G A. , Abramovich G. , Bing Yu. and Tu P H. , "Stand-Off Iris Recognition System", Second IEEE International Conference on Biometric Theory, Applications and Systems, 2008, pp: 1-7.
  14. Abdullah, Mohammed A M. , Al-Dulaimi, F H A. , Al-Nuaimy, Waleed. and Al-Ataby Ali. , "Smart Card with Iris Recognition for Hifh Security Access Environment," IEEE International Conference on Biomedical Engineering, 2011, pp: 382-385.
  15. MMU Iris Database, http://pesona. mmu. edu. my/~ccteo/
  16. Gonzalez, Woods, R. C. dan. , R. E. , Digital Image Processing 2nd/ed. , Prentice-Hall. Inc. , Upper Saddle River, New Jersey, 2002.
  17. Ganeshan, B. , Theckedath, D. , Young, R. , Chatwin, C. , "Biometric iris recognition system using a fast and robust iris localization and alignment procedure", Optics and Lasers in Engineering, Vol. 44, 2006, pp: 1-24.
  18. Masek, L. ,"Recognition of Human Iris Patterns for Biometric Identification", Thesis, School of Computer Science and Software Engineering, University of Western Australia, 2003.
  19. Roy, K . , Bhattacharya, P. , Suen, Ching Y. , "Towards nonideal iris recognition based on level set method, genetic algorithms and adaptive asymmetrical SVMs" Elsevier Engineering Applications of Artificial Intelligence, Vol. 24, 2011, pp: 458-475.
  20. Nabti, M. , Bouridane, A. , "An effective and fast iris recognition system based on a combined multiscale feature extraction technique", Pattern Recognition, Vol. 44, 2008, pp: 868-879.
  21. Birgale, L. V. , Kokare, M. , "Iris recognition using discrete wavelet transform", IEEE Trans. an International Conference on Digital Image Processing(ICDIP), 2009, pp: 147-151.
  22. Wheeler, F M. , Perera, A G A. , Abramovich G. , Bing Yu. and Tu P H. , "Stand-Off Iris Recognition System", Second IEEE International Conference on Biometric Theory, Applications and Systems, 2008, pp: 1-7.
  23. Zhang, P. , Li, De. , Wang, Qi. , "A Novel Iris recognition Method Based on Feature Fusion", IEEE Proceedings of the Third International Conference on Machine Learning and Cybernetics, Shanghai, August 2004, pp:3661-3665.
  24. MATLAB The Language of Technical Computing, The Mathworks.
Index Terms

Computer Science
Information Sciences

Keywords

Threshold Image Morphology Optimal Level Decomposition Wavelet Coefficients Correlation Selective Iris Features

Powered by PhDFocusTM