We apologize for a recent technical issue with our email system, which temporarily affected account activations. Accounts have now been activated. Authors may proceed with paper submissions. PhDFocusTM
CFP last date
20 November 2024
Call for Paper
December Edition
IJCA solicits high quality original research papers for the upcoming December edition of the journal. The last date of research paper submission is 20 November 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

Iris Texture Analysis for Security Systems

by Vanaja Roselin. E. C, L. M. Waghmare
journal cover thumbnail

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 64 - Number 22
Year of Publication: 2013
Authors: Vanaja Roselin. E. C, L. M. Waghmare
10.5120/10779-5507

Vanaja Roselin. E. C, L. M. Waghmare . Iris Texture Analysis for Security Systems. International Journal of Computer Applications. 64, 22 ( February 2013), 37-44. DOI=10.5120/10779-5507

@article{ 10.5120/10779-5507,
author = { Vanaja Roselin. E. C, L. M. Waghmare },
title = { Iris Texture Analysis for Security Systems },
journal = { International Journal of Computer Applications },
issue_date = { February 2013 },
volume = { 64 },
number = { 22 },
month = { February },
year = { 2013 },
issn = { 0975-8887 },
pages = { 37-44 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume64/number22/10779-5507/ },
doi = { 10.5120/10779-5507 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T21:17:22.196859+05:30
%A Vanaja Roselin. E. C
%A L. M. Waghmare
%T Iris Texture Analysis for Security Systems
%J International Journal of Computer Applications
%@ 0975-8887
%V 64
%N 22
%P 37-44
%D 2013
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Biometric security is highly reliable and secure system. Proposed work, efficient methods for pupil detection and wavelet transformation with five-level decomposition for feature extraction are proposed and which results with accurate feature vector are stored as bits and then processes for identification and verification. Statistical performance evaluation using parameters and classifier used hamming distance for matching the patterns efficiently with stored database . We use CASIA database.

References
  1. J. Daugman," How Iris Recognition works", proceedings of 2002 International conference on Image processing, vol. 1, 2002.
  2. J. Daugman," High confidence visual recognition of persons by a Test of statistical Independence", IEEE Transactions on pattern analysis and machine intelligence, vol. 15, no. 11, Nov 1993, pp1148-1161.
  3. Li. Ma, et al. , "Local Intensity Variation Analysis for Iris Recognition", Elsevier- Pattern Recognition, vol. 37, No. 6, pp. 1287-1298, 2004.
  4. S. Lim, K. Lee, O. Byeon, T. Kim, "Efficient Iris Recognition through Improvement of Feature Vector and Classifier", ETRI Journal, Vol. 23, No. 2, June 2001, pp. 61-70.
  5. W. Boles and B. Boashash,"A Human Identification Technique using Images of the Iris and wavelet transform", IEEE Transactions on signal processing, Vol. 46, No. 4, April 1998.
  6. Karu K, Anil Jain K, and Bolle R M," Is there any texture in the Image?", IEEE Transactions on Pattern Recognition, Vol. 29, No. 9, pp. 1437-1446, 1996.
  7. R. Wildes et al. , "Machine Vision System for Iris Recognition", Machine Vision and Applications, Vol. 9, pp. 1-8, 1996.
  8. R. P. wildes," Iris Recognition: An Emerging Biometric Technology", Proceeding of the IEEE, vol. 85, pp 1348-1363, 1999.
  9. J. Daugman," How Iris Recognition works", IEEE Transactions on Circuits and systems for video Technology, Vol. 14, No. 1, Jan 2004.
  10. Richard Yew Fatt Ng, Yong Hour Tay, Kai Ming Mok," A Review if Iris Recognition Algorithm", IEEE Transaction, DOI 978-1-4244-2328-6/08, 2007.
  11. R. Wildes, J. Asmuth, G. Green,S. Hsu, R. Kolczynski, J. Matey and S. McBride,"A machine-vision system for Iris Recognition", Machine vision and Applications, vol. 9, pp1-8,1996.
  12. Robert W. Ives, Anthony J. Guidry and Delores M Etter, "Iris Recognition using Histogram Analysis", IEEE conference on signal, system and computer ,2004, pp. 562-566.
  13. A. Poursaberi and H. N. Araabi, "Iris Recognition for Partially Occluded Methodology and Sensitivity Analysis", EURASIP journal on "Advances in Signal processing, Vol. 2007, Article ID 36751, 2005.
  14. A. Poursaberi and B. N. Araabi, "A Half Eye Wavelet Based for Iris Recognition" proceeding of the 2005,5th International Conference on Intelligent Systems Design and Applications (ISDA'05).
  15. Amol D. Rahulkar, R. S. Holambe, "Half-Iris Feature Extraction and Recognition using a New Class of Biorthogonal triplet Half-Band Filter Bank and Flexible k-out-of-n: A postclassifier", IEEE Transactions on Information Forensics and Security, Vol. 7, No. 1, Feb 2012.
  16. Li Ma, T. Yunhong Wang, and D. Zhang. "Personal identification based on iris texture analysis", IEEE Transactions on Pattern Analysis and machine Intelligence, vol. 25, no. 12, 2003.
  17. S. Mallat, W. Hwang, "singularity detection and processing with wavelet", IEEE Transaction on information Theory, 38(2):617-643, 1992.
  18. Md. Rabiul Islam, Dr. Wang Yin Chai, Asma Khatun," Partial Iris Image Recognition Using Wavelet Based Texture Features", International Conference on Intelligent and Advance Systems (ICIAS) ,2010.
  19. Jafar M. H. Ali, Aboul Ella Hassanien," An Iris Recognition System to Enhance E-security Environment Based on Wavelet Theory", AMO-Advance Modeling and Optimization, vol. 5, No. 2, 2003.
  20. Mayank vatsa, Richa singh, Afzel Noore," Improving Iris recognition performance using segmentation, Quality Enhancement, Match Score Fusion, and Indexing", IEEE Transactions on Systems, Man, and Cybernetics B, Cybern. , vol. 38, no. 4, pp. 1021-1034, Aug. 2008.
  21. Makram Nabti, Lahouari Ghouti and Ahmed Bouridane," An effective and fast iris recognition system based on a combined multiscale feature extraction technique", Elsevier-Pattern Recognition 41, (2008) 868-879.
  22. Kevin W. Bowyer, Karen Hollingsworth, Patrick J. Flynn," Image understanding for iris biometrics: A survey", Elsevier computer vision and Image Understanding 110(2008) 281-307.
  23. Li Ma, Tieniu Tan, Yunhong Wang and Dexin Zhang, "Efficient Iris Recognition by Characterizing Key Local Variations", IEEE Transactions on Image processing, Vol. 13, No. 6, June 2004.
  24. Shimaa M. Elsherief, Mahmoud E. Allam, Mohamed W. Fakhr, "Biometric Personal identification Based on Iris Recogition", International conference on computer Engineering and Systems, on page 208-213, 5-7 Nov, 2006.
  25. John Daugman, "Probing the Uniqueness and Randomness of IrisCodes: Results from 200 Billion Iris Pair Comparisons", Proceedings of the IEEE, Vol. 94, Issue: 11, pages: 1927-1935, Nov 2006.
  26. L. Ma, Y. wang, T. Tan," Iris recognition Based on multichannel Gabor Filtering", Proc. of the 5th Asian conference on computer vision, vol. I, pp. 279-283, 2002.
  27. J. Daugman, "Statistical Richness of Visual Phase Information: Update on recognizing persons by Iris patterns", International Journal of computer vision, Vol. 45, No. 1, pp. 25-38,2001.
  28. L. Ma, Y. wang, T. Tan," Iris Recognition using Circular Symmetric Filters", proc. of the 16th International Conference on pattern recognition, vol. II, pp. 414-417,2002.
  29. http://www. sinobiometrics. com/resources. htm.
Index Terms

Computer Science
Information Sciences

Keywords

Feature extraction haar wavelet transformation FAR FRR Feature vector size Computational time

Powered by PhDFocusTM