Development of an Iris-Based Access Control System Using a Two-Level Segmentation Approach

International Journal of Computer Trends and Technology (IJCTT)          
© - May Issue 2013 by IJCTT Journal
Volume-4 Issue-5                           
Year of Publication : 2013
Authors :Falohun A. S, Omidiora E.O, Fakolujo A.O, dOjo.J.A


Falohun A. S, Omidiora E.O, Fakolujo A.O, dOjo.J.A "Development of an Iris-Based Access Control System Using a Two-Level Segmentation Approach"International Journal of Computer Trends and Technology (IJCTT),V4(5):1318-1326 May Issue 2013 .ISSN Published by Seventh Sense Research Group.

Abstract: - Security of lives and assets has become a very interesting issue worldwide. Ability to restrict access to unauthorized users via an identification system that cannot be compromised at a very fast rate is highly desirable because it can be very costly if not achievable. In this work, a new segmentation technique that is suitable for segmenting black people`s irises was developed. The system was simulated using irises of black people`s faces captured in Nigeria and iris images from Chinese Academy of Sciences Institute of Automation (CASIA [1]), a standard iris database. The False Acceptance Rate(FAR) and False Rejection Rate(FRR) of the two image databases were obtained with varying Hamming Distances of 0.26, 0.30, 0.35, 0.39 and 0.45 respectively.


[1] Chinese Academy of Sciences – Institute of Automation., (2003), “Database of 756 Greyscale Eye Images.”, Version 1.0.
[2] Ahmad. M. Sarhan (2009), “Iris Recognition using Discrete Cosine Transform and Artificial Neural Networks”, Journals of Computer Science, 5:369 – 373.
[3] Williams, G., (2000), “Iris Recognition Technology”, Proceedings of the 15th International Conference on Pattern Recognition, 7: 56.
[4] Khin S. (2009) “Iris Recognition System using Statistical features for Biometric and Identification”: International Conference On Electronic Computer Technology, IEEE pp. 554 – 556.
[5] Anil, K.J., Aarun, R. and Safir, P., (2004), ”An Introduction to Biometric Recognition”, 14(1): 321-324.
[6] Daugman J. (2003). The importance of being random: Statistical principles of Iris Recognition”. Pattern Recognition. 36(2): 279 – 291.
[7] Wolff, E., (1976), Anatomy of the Eye and Orbit., 7th edition. H. K. Lewis & Co. Ltd, New York.
[8] Nitin, K. and Nandita, B. (2009), “An efficient and accurate Iris segmentation Technique.” Digital Image Computing: Techniques and Applications, IEEE computer society, 347-352.
[9] Bertillon (1885), “Person Identification Technique using human Iris Recognition”,
[10] Daugmann. J. (2001) “High Confidence Visual Recognition of persons by a test of statistical independence, “ IEEE Transactions on pattern analysis and machine intelligence, 15(11):1148 – 1161.
[11] Wildes R. (1997) “Iris Recognition An Emerging Biometric Technology”, proceeding of the IEEE, 85(a): 1348 – 1363.
[12] Boles, W. and Boashash, B. (1998), “A Human Identification Technique using Images of the Iris and Wavelet Transform.”, IEEE Transactions on Signal Processing, 46 (4): 457- 459.

Keywords — Biometrics, Iris Recognition, Segmentation, Authentication, Morphological.