International Journal of Computer
Trends and Technology

Research Article | Open Access | Download PDF

Volume 4 | Issue 5 | Year 2013 | Article Id. IJCTT-V4I5P70 | DOI : https://doi.org/10.14445/22312803/IJCTT-V4I5P70

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

Falohun A. S, Omidiora E.O, Fakolujo A.O, dOjo.J.A

Citation :

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), vol. 4, no. 5, pp. 1318-1326, 2013. Crossref, https://doi.org/10.14445/22312803/IJCTT-V4I5P70

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.

Keywords

Biometrics, Iris Recognition, Segmentation, Authentication, Morphological.

References

[1] Chinese Academy of Sciences – Institute of Automation., (2003), “Database of 756 Greyscale Eye Images.”, http://www.sinobiometrics.com 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 Identification”: for Biometric and 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”,  citeseerx.ist.psu.edu/viewdoc/summary.
[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.
[13] Tisse C., Martin L, Torres L. and Robert M. (2002) “Personal Identification technique using human iris recognition”, In proceedings of ICVI’ 02, pp. 294 – 299
[14] Zhu, Y., Tan, T., Wang, Y., (2000), “Biometric personal Identification based on Iris Patterns.” Proceedings of the 15th International Conference on Pattern Recognition, (ICPR’00)- 2: 2801.video sequences.”, Journal of Electronic Imaging., 19(3):1-15.
[15] Lim S., Pae K., Lee K., Byeon O. and Kim. T., (2001) “Efficient Iris recognition through improvement of feature vector and classifier”, ETRI Journal, 23(2): 61 – 70.
[16] Daugman J., (1993) “High Confidence Visual Recognition of persons by a test of Statistical indepencence”. IEEE Transactions on Pattern Analysis and Machine Intelligence, 1148 – 1161, November 1993.
[17] Michal Dobes  and Libor Machala, (2004) Upol iris image database. http:// phoenix.  Inf.upol.cz/iris/
[18]  Proenca Hugo and Alexandre Luis A., (2005) Ubiris A noisy iris image databae. IN proceedings of the 13th international conference on image analysis and processing (ICIAP 2005) : 970 – 977, Calgary.
[19] Bourennane S., Fossati C., Ketchantang W. (2010), “New Algorithm for Iris Recognition based on video sequences.”, Journal of Electronic Imaging., 19(3):1-15.
[20]  Falohun A.S.(2012). Development of a Feature Extraction Method for Iris Recognition using Enhanced Inverse Analytical Fourier-Mellin Transform. Unpublished Ph.D.Thesis.