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Contourlet Transform for Iris Image Segmentation

by Behrooz Zali-vargahan, Mehdi Chehel Amirani, Hadi Seyedarabi
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 60 - Number 10
Year of Publication: 2012
Authors: Behrooz Zali-vargahan, Mehdi Chehel Amirani, Hadi Seyedarabi
10.5120/9732-4209

Behrooz Zali-vargahan, Mehdi Chehel Amirani, Hadi Seyedarabi . Contourlet Transform for Iris Image Segmentation. International Journal of Computer Applications. 60, 10 ( December 2012), 41-44. DOI=10.5120/9732-4209

@article{ 10.5120/9732-4209,
author = { Behrooz Zali-vargahan, Mehdi Chehel Amirani, Hadi Seyedarabi },
title = { Contourlet Transform for Iris Image Segmentation },
journal = { International Journal of Computer Applications },
issue_date = { December 2012 },
volume = { 60 },
number = { 10 },
month = { December },
year = { 2012 },
issn = { 0975-8887 },
pages = { 41-44 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume60/number10/9732-4209/ },
doi = { 10.5120/9732-4209 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T21:06:15.604778+05:30
%A Behrooz Zali-vargahan
%A Mehdi Chehel Amirani
%A Hadi Seyedarabi
%T Contourlet Transform for Iris Image Segmentation
%J International Journal of Computer Applications
%@ 0975-8887
%V 60
%N 10
%P 41-44
%D 2012
%I Foundation of Computer Science (FCS), NY, USA
Abstract

The aim of this paper is improving the iris segmentation with the Contourlet transform. At first iris segmentation performed by canny edge detector and Hough Transform. By this approach some images don't segmented properly, so we want to find a way to correct the image segmentation failures. Before applying edge detector, Contourlet transform applied for image denoising. By this approach, %100 accuracy rate in iris image segmentation is obtained. Denoised image with Contourlet transform a little blurred. After image denoised and image segmented, for keep basic quality of the image, corresponded basic image and the segmented image. So, segmentation will be right on the main image.

References
  1. Ma, L. , Tan, T. , Wang, Y. , Zhang, D. : 'Personal identification based on iris texture analysis, IEEE Trans. Pattern Anal. Mach. Intell. , 2003, 25,(12), pp. 1519 – 1533
  2. J. Zuo, N. D. Kalka, and N. A. Schmid, "A robust iris segmentation procedure for unconstrained subject presentation," Biometric Consortium Conference, 2006 Biometrics Symposium: Special Session on Research, pp. 1–6, Sept. 19 2006-Aug. 21 2006.
  3. CASIA Iris Image Database, http://www. cbsr. ia. ac. cn/irisdatabase. htm,2009.
  4. J. G. Daugman, "High con?dence visual recognition of persons by a test of statistical independence," IEEE Trans. Pattern Anal. Mach. Intell. , vol. 15, no. 11, pp. 1148–1160, Nov. 1993.
  5. J. G. Daugman, "Demodulation by complex-valued wavelets for stochastic pattern recognition," Int. J. Wavelets, MultiResol. Inf. Process. ,vol. 1, no. 1, pp. 1–17, Jan. 2003.
  6. R. P. Wildes, "Iris recognition: An emerging biometric technology,"Proc. IEEE, vol. 85, no. 9, pp. 1348–1363, Sep. 1997.
  7. L. Masek, "Recognition of human iris patterns for biometric identi?cation," B. S. dissertation, The School of Computer Science and Software Engineering, The University of Western Australia, Crawley WA, Perth,Australia, 2003.
  8. L. Ma, Y. Wang, and T. Tan, "Iris recognition using circular symmetric ?lters," in Proc. 16th Int. Conf. Pattern Recogn. (ICPR), Quebec City,Canada, Aug. 2002, vol. 2, pp. 805–808.
  9. S. Lim, K. Lee, O. Byeon, and T. Kim, "Ef?cient iris recognition through improvement of feature vector and classi?er," J. Electron. Telecommun. Res. Inst. , vol. 33, no. 2, pp. 61–70, Jun. 2001.
  10. L. Ma, T. Tan, and Y. Wang, "Ef?cient iris recognition by characterizing key local variations," IEEE Trans. Image Process. , vol. 13, no. 6,pp. 739–750, Jun. 2004.
  11. J. Huang, L. Ma, Y. Wang, and T. Tan, "Iris model based on local orientation description," in Proc. Asian Conf. Comput. Vision , Korea,Apr. 2004, pp. 954–959.
  12. X. Yuan and P. Shi, "Iris feature extraction using 2-D phase congruency," in Proc. Third Int. Conf. Inf. Technol. Appl. (ICITA), Sydney,Australia, Jul. 2005, vol. 33, pp. 437–441.
  13. Do, M. N. , & Vetterli, M. (2003). Contourlets beyond wavelets. New York: J. Stoeckler and G. V. Welland, Eds. Academic Press.
  14. J. Thornton, M. Savvides, and B. V. Kumar, "Robust iris recognition using advanced correlation techniques," in Proc. Second Int. Conf. Image Anal. Recogn. (ICIAR), Toronto, Canada, Sep. 2005, vol. 3656,pp. 1098–1105, Springer Berlin/Heidelberg.
  15. J. Huang, Y. Wang, T. Tan, and J. Cui, "A new iris segmentation method for recognition," in Proc. 17th Int. Conf. Pattern Recogn. (ICPR) , Cambridge, U. K. , Aug. 2004, vol. 3, pp. 23–26.
  16. A. Abhyankar and S. Schuckers, "Active shape models for effective iris segmentation," in Proc. SPIE Conf. Biometric Technol. Human Identif. III, Orlando, FL, Apr. 2006, pp. 62020H. 1–62020H. 10.
  17. W. Boles and B. Boashash, "A human identi?cation technique using images of the iris and wavelet transform," IEEE Trans. Signal Process. ,vol. 46, no. 4, pp. 1185–1188, Apr. 1998.
  18. K. Bae, S. Noh, and J. Kim, "Iris feature extraction using independent component analysis," in Proc. 4th Int. Conf. Audio and VideoBased Biometric Person Authentic. (AVBPA), Guildford, U. K. , 2003,pp. 838–844.
  19. V. Dorairaj, N. A. Schmid, and G. Fahmy, "Performance evaluation of iris based recognition system implementing PCA and ICA encoding techniques," in Proc. SPIE Conf. Biometric Technol. Human Identif. III, Orlando, FL, Apr. 2005.
  20. Z. He, Z. Sun, T. Tan, X. Qiu, C. Zhong, and W. Dong, "Boosting ordinal features for accurate and fast iris recognition," in Proc. IEEE Comput. Soc. Workshop Biometrics at the Computer Vision Pattern Recogn. Conf. , 2008.
Index Terms

Computer Science
Information Sciences

Keywords

Canny edge detector Contourlet transform Hough transform iris recognition iris segmentation

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