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

Submit your paper
Know more
Reseach Article

Automated Iris Recognition System: An Overview

by Bhagyashri S. Satpute, B. D. Jadhav
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 115 - Number 17
Year of Publication: 2015
Authors: Bhagyashri S. Satpute, B. D. Jadhav
10.5120/20247-2612

Bhagyashri S. Satpute, B. D. Jadhav . Automated Iris Recognition System: An Overview. International Journal of Computer Applications. 115, 17 ( April 2015), 50-54. DOI=10.5120/20247-2612

@article{ 10.5120/20247-2612,
author = { Bhagyashri S. Satpute, B. D. Jadhav },
title = { Automated Iris Recognition System: An Overview },
journal = { International Journal of Computer Applications },
issue_date = { April 2015 },
volume = { 115 },
number = { 17 },
month = { April },
year = { 2015 },
issn = { 0975-8887 },
pages = { 50-54 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume115/number17/20247-2612/ },
doi = { 10.5120/20247-2612 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:55:10.063642+05:30
%A Bhagyashri S. Satpute
%A B. D. Jadhav
%T Automated Iris Recognition System: An Overview
%J International Journal of Computer Applications
%@ 0975-8887
%V 115
%N 17
%P 50-54
%D 2015
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Iris texture pattern can be used for biometric verification and identification of a person from a large dataset. Iris recognition is used in several fields, like border, security prone, industrial and medical institutes etc. Due to its high correctness and uniqueness, it is used in several fields of access control and border area security. The demand for iris recognition is increasing continuously due to its reliability, accuracy and uniqueness. To improve the overall recognition rate and performance of iris recognition system, the researchers have to work in different aspects like unconstrained environment, noisy images as well as blurred images. This paper overviews the different steps involve into iris recognition system as well as various methodology presents in the iris recognition system.

References
  1. John Daugman, "Statistical richness of visual phase information: updateon recognizing persons by iris patterns," International Journal of Computer Vision, vol. 45, no. 1, pp. 25-38, 2001.
  2. John Daugmann, "How iris recognition works," IEEE Trans. Circuits Syst. Video Technol. ,vol. 14, no. 1, pp. 21-30, 2004.
  3. Shaabad A. Sahmoud and Ibrahim S. Abuhaiba, "Efficient iris segmentation method in unconstrained environments," Pattern Recognition, vol. 46, no. 12, pp. 3174-3185, 2013.
  4. Mohamad-Ramli, N. A. , M. S. Kamarudin and A. Joret, 2008. "Iris Recognition for Personal Identification", The International Conference on Electrical Engineering (ICEE), July 6-10, 2008, OKINAWA, JAPAN.
  5. AziziA. and H. Reza, 2009. "Efficient IRIS Recognition through Improvement of Feature Extraction and subset Selection", (IJCSIS) International Journal of Computer Science and Information Security, 2: 1.
  6. Lagree, S. and K. W. Bowyer, 2010. "Ethnicity prediction based on iris texture features", In: 22nd Midwest Artificial Intelligence and Cognitive Science Conference (MAICS).
  7. Richard Yew Fatt Ng, Yong Haur Tay and Kai Ming Mok, " A review of iris recognition algorithms," IEEE Trans. Information Technol. , vol. 2, pp. 1-7, 2008.
  8. Jing Huang, Xinge You, Yuan Yan Tang, Liang Du and Yaun Yaun, "A novel iris segmentation using radial-suppression edge detection," Signal Processing, vol. 89, no. 12, pp. 2630-2643, 2009.
  9. J. Canny, "A computational approach to edge detection," IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 8, no. 6, pp. 679-698, 1986.
  10. Annapoorani, G. , R. Krishnamoorthi, P. G. Jeya and Petchiammal, 2010. "Accurate and Fast Iris Segmentation", International Journal of Engineering Science and Technology, 2(6): 1492-1499.
  11. Naphtali Rishe and Jean Andrian, "A highly accurate and computationally efficient approach for unconstrained iris segmentation," Image and Vision Computing, vol. 28, no. 2, pp. 261-269, 2010.
  12. S. Lim, K. Lee, O. Byeon, and T. Kim (2001). "Efficient Iris Recognition through Improvement of Feature Vector and Classifier", ETRI Journal, vol. 23, no. 2, pp. 61-70.
  13. H. Sung, J. Lim, J. Park, and Y. Lee (2004). "Iris Recognition Using Collarette Boundary Localization", Proceedings of the 17th International Conference on Pattern Recognition, vol. 4, pp. 857-860.
  14. M. S. Crouse, R. D. Nowak, and R. G. Baraniuk, 1998 "Wavelet-based statistical signal processing using hidden Markov models", IEEE Trans. Signal Process. , vol. 46, no. 4, pp. 886–902.
  15. D. M. Rankin, B. W. Scotney, P. J. Morrow and B. K. Pierscionek, "Iris recognition failure over time: The effects of texture," Pattern Recognition, vol. 45, no. 1, pp. 145-150, 2012.
  16. John Daugman "High confidence visual recognition of persons by a test of statistical independence," IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 15, no. 11, 1993.
  17. L. Ma, T. Tan, Y. Wang and D. Zhang, "Personal identification based on iris texture analysis," IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 25, no. 12, pp. 1519-1533, 2004.
  18. Y. Zhu, T. Tan, and Y. Wang (2000). "Biometric Personal Identification Based on Iris Patterns", Proceedings of the 15th International Conference on Pattern Recognition, vol. 2, pp. 2801-2804.
Index Terms

Computer Science
Information Sciences

Keywords

Acquisition Localization Iris recognition Feature Extraction Matching.