CFP last date
20 December 2024
Call for Paper
January Edition
IJCA solicits high quality original research papers for the upcoming January edition of the journal. The last date of research paper submission is 20 December 2024

Submit your paper
Know more
The week's pick
Responsive image
Improved Shuffled Frog Leaping Algorithm with Self-Adaptive Shuffling for Fuzzy Logic PD+G Controller Optimization in Robotic Manipulators

Duc Hoang Nguyen
Random Articles
Reseach Article

Robust Iris Recognition based on Orientation Field

by Pravin S. Patil
journal cover thumbnail

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 95 - Number 19
Year of Publication: 2014
Authors: Pravin S. Patil
10.5120/16703-6844

Pravin S. Patil . Robust Iris Recognition based on Orientation Field. International Journal of Computer Applications. 95, 19 ( June 2014), 19-24. DOI=10.5120/16703-6844

@article{ 10.5120/16703-6844,
author = { Pravin S. Patil },
title = { Robust Iris Recognition based on Orientation Field },
journal = { International Journal of Computer Applications },
issue_date = { June 2014 },
volume = { 95 },
number = { 19 },
month = { June },
year = { 2014 },
issn = { 0975-8887 },
pages = { 19-24 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume95/number19/16703-6844/ },
doi = { 10.5120/16703-6844 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:19:52.541571+05:30
%A Pravin S. Patil
%T Robust Iris Recognition based on Orientation Field
%J International Journal of Computer Applications
%@ 0975-8887
%V 95
%N 19
%P 19-24
%D 2014
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Recently, with an increasing demand on security biometric personal identification has been receiving extensive attention. Among many biometrics techniques, iris recognition is one of the most promising approached due to its high reliability. This paper present a robust iris recognition technique based on orientation field. Initially the eye images have been localized in circular form by using Hough transform. Than flat bed form of iris is generated using Daugman's homogeneous rubber sheet model. From the view point of texture analysis, the local spatial patterns in an iris mainly involve orientation and frequency information. Local image structure plays an important role in iris recognition, so an intuitive idea of iris pattern representation is based on the geometric structure of image data in small region. In our work localized iris image is divided into number of non-overlapping blocks. The blocks orientation has been determined from the pixel gradient orientation based on averaging and optimization. The gradient magnitudes have been computed using Sobel gradient operators. The variance of orientation has been used as feature vector. L2 norm is used to compute a similarity score for the query and template images. The performance of the implemented algorithms has been evaluated using Receiver Operating Characteristics (ROC) and experimental results are reported.

References
  1. A. K. Jain, Ross A. ,Prabhakar S. "An Introduction to Biometric Recognition",IEEE Transction on Circuits and System for Video Technology-Special issue on Image and Video-Based Biometrics,vol. 14,issue. 1,2004
  2. S. Sanderson,J. Erbetta,"Authentication for Secure Environments Based on Iris Scanning Technology",IEEE Colloquium on Visual Biometrics,2000
  3. A. K. Jain,R. M. Bolle and S. Pankanti, "Biometric: Personal Identification in a Networked Society", Eds. Norwell MA:Kluswer, 1999
  4. D. Zhang, "Biometrics Technologies and Application",Proceeding of International Conference on Image and Graphics,pp. 42-49,Tianjing,China,August 2000
  5. H. Davision, "The Eye",Academic,Landon,1962
  6. F. H. Adler,"Physiology of the Eye: Clinical Application,Fourth ed. Landon,The C,V. Mosby Company,1965
  7. J. Daugman, "How Iris recognition works," Proceeding of International Conference on Image processing, vol. no. 1, 2002.
  8. J. Daugman, "High confidence visual recognition of person by a test of statistical independence," IEEE Trans. Pattern analysis and machine intelligence, vol. 15,no. 11,pp1148-1161, Nov. 1993.
  9. J. Daugman,"Demodulation by Complex-Valued Wavelets for Stochastic Pattern Recognition," Int'l J. Wavelets, Multi-resolution and Information Processing, vol. 1, no. 1, pp 1-17, 2003.
  10. W. W. Boles, B. Boashah, "A human identification technique using of the Iris and wavelet transform," IEEE Trans. on signal processing vol. 46, no. 2,pp1185-1188 Apr. 1998.
  11. R. P. Wildes, "Iris Recognition: An Emerging Biometric Technology", Proceedings of the IEEE, vol. 85, pp. 1348-1363, Sept. 1997.
  12. L Ma, Tieniu Tan, Yunhong Wang," Efficient Iris Recognition by Characterizing Key Local Variations," IEEE Trans. on Image Processing, vol. 13, no. 6, pp 739-750, June 2004
  13. L. Ma, Y. Wang, T. Tan, "Iris recognition using circular symmetric filters," National laboratory of pattern recognition ,Institute of automation, Chinese academy of sciences, 2002
  14. L. Ma, Y. Wang, and T. Tan, "Iris Recognition Based on Multichannel Gabor Filtering," Proceedings Fifth Asian Conf. Computer Vision, vol. I, pp 279-283, 2002.
  15. L Ma, Tieniu Tan, Yunhong Wang," Personal Identification Based on Iris Texture Analysis," IEEE Transaction on Pattern analysis and machine intelligence, vol. 25, no. 12, pp 1519-1533, December 2003.
  16. R. Wildes, J. Asmuth, G. Green, S. Hsu, R. Kolczynski, J. Matey, S. McBride, "A Machine-Vision system for automated Iris recognition," Proceeding Machine Vision and Application,vol. 9,pp 1-8,1996
  17. L. Masek, "Recognitions of Human Iris Patterns for Biometric Identifications [B]", School of Computer Science and Software Engineering, The University of Western Australia, 2003.
  18. "CASIA Iris Image Database", Institute of Chinese Academy of Sciences, http://www. sinobiometrics. com/2004
  19. M. Ezhilarasan, R. Jacthish, K. S. Ganbathy Subramaniam, R. Umapathy "Iris Recognition Based on its Texture Patterns" International Journal on Computer Science and Engineering,vol. 2,issue. 9,pp. 3071-3074,2010
  20. R. Wildes, J. Asmuth, G. Green, S. Hsu, R. Kolczynski, J. Matey, S. McBride, "A system for automated Iris recognition," Proceeding IEEE Workshop on Application of Computer Vision,Sarasota,FL,pp. 121-128,1994
  21. W. Kong, D. Zhang, "Accurate Iris segmentation based on novel reflection and eyelashes detection model," Proceeding of 2001 International symposium on intelligent multimedia, video and speech processing Hong Kong, 2001.
  22. C. Tisse, L. Martin, L. Jorres, M. Robert, "Person identification technique using human Iris recognition," International conference on vision interface Canada, 2002.
  23. Iris Recognition:Unwrapping the Iris http://cnx. org/content/m12492/latest, 26/10/2006
  24. H. Sung, J. Lim, Y. Lee, "Iris recognition using collarette boundary localization," Proceeding of the 17th International conference on pattern recognition (ICPR-04)
  25. P. Perona, " Orientation Diffusion",IEEE Transction on Image Processing,vol. 7,pp. 457-467,1998
  26. P. E. Trahanias and A. N. Venetsanopoueos " Vector Directional Filters", IEEE Transction on Image Processing,vol. 2,pp 528-534,1993
  27. S. Noh,K. Boe and J. Kim, " A Novel Method to Extraction Features for Iris Recognition System" AVBPA-2003,pp. 838-844
  28. Z. Sun,Y. Wang,T. Tan,J. Cui " Robust Direction Estimation of Gradient Vector Field for Iris Recognition" IEEE International Conference, 2004
  29. G. Hong-Ying,Z. Yue-ting,P. Yun-he "An Iris Recognition Method Based on Multi-Orientation Features and Non-Symmetrical SVM, Journal of Zhejiang University SCI 2005 6A(5):428-432
  30. C. Sanchez-Avila and R. Sanchez-Reillo, "Two Different Approaches for Iris Recognition using Gabor Filters and Multiscale Zero-crossing Representation", Journal of the Pattern Recognition 38,pp. 231-240, 2005
Index Terms

Computer Science
Information Sciences

Keywords

Iris Image Preprocessing Orientation field Feature Variance Receiver Operating Characteristics

Powered by PhDFocusTM