A Novel Approach to Iris Localization for Iris Biometric Processing

Authors: Somnath Dey, Debasis Samanta

Abstract:

Iris-based biometric system is gaining its importance in several applications. However, processing of iris biometric is a challenging and time consuming task. Detection of iris part in an eye image poses a number of challenges such as, inferior image quality, occlusion of eyelids and eyelashes etc. Due to these problems it is not possible to achieve 100% accuracy rate in any iris-based biometric authentication systems. Further, iris detection is a computationally intensive task in the overall iris biometric processing. In this paper, we address these two problems and propose a technique to localize iris part efficiently and accurately. We propose scaling and color level transform followed by thresholding, finding pupil boundary points for pupil boundary detection and dilation, thresholding, vertical edge detection and removal of unnecessary edges present in the eye images for iris boundary detection. Scaling reduces the search space significantly and intensity level transform is helpful for image thresholding. Experimental results show that our approach is comparable with the existing approaches. Following our approach it is possible to detect iris part with 95-99% accuracy as substantiated by our experiments on CASIA Ver-3.0, ICE 2005, UBIRIS, Bath and MMU iris image databases.

Keywords: Iris recognition, iris localization, biometrics, image processing.

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1084644

References:

[1] J. G. Daugman, "High Confidence Visual Recognition of Persons by a Test of Statistical Independence," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 15, pp. 1148-1161, November 1993.
[2] J. Daugman, "How iris recognition works," IEEE Transactions on Circuits and Systems for Video Technology, vol. 14, no. 1, pp. 21- 30, 2004.
[3] P. Hough, "Method and means for recognizing complex patterns." U.S. Patent 3,069,654, December 1962.
[4] R. P. Wildes, "Iris Recognition: An Emerging Biometric Technology," Proceedings of the IEEE, vol. 85, pp. 1348-1363, September 1997.
[5] L. Ma, T. Tan, Y. Wang, and D. Zhang, "Efficient Iris Recognition by Characterizing Key Local Variations," IEEE Transactions on Image Processing, vol. 13, pp. 739-750, June 2004.
[6] L. Masek, "Recognition of human iris patterns for biometric identification." http://www.csse.uwa.edu.au/ pk/studentprojects/libor, 2003.
[7] C.L.Tisse, L.Martin, L.Torres, and M.Robert, "Person Identification Technique Using Human Iris Recognition," in Proceedings of Vision Interface, (Canada), pp. 294-299, 2002.
[8] H. Sung, J.Lim, J.Park, and Y.Lee, "Iris Recognition Using Collarette Boundary Localization," in Proceedings of 17th International Conference on Pattern Recognition (ICPR-04), vol. 4, pp. 857-860, August 2004.
[9] J. Cui, Y. Wang, T. Tan, L. Ma, and Z. Sun, "An iris recognition algorithm using local extreme points," in First International Conference Biometric Authentication (D. Zhang and A. K. Jain, eds.), vol. 3072 of Lecture Notes in Computer Science, pp. 442-449, Springer, 2004.
[10] J. M. H. Ali and A. E. Hassanien, "An Iris Recognition System to Enhance E-security Environment Based on Wavelet Theory," AMO - Advanced Modeling and Optimization journal, vol. 5, no. 2, pp. 93- 104, 2003.
[11] T. M¨aenp¨a¨a, "An Iterative Algorithm for Fast Iris Detection," in Advance in Biometric Person Authentication,LNCS 3781, vol. 5404, pp. 127-134, 2005.
[12] J. Kim, S. Cho, J. Choi, and I. Robert J. Marks, "Iris recognition using wavelet features," J. VLSI Signal Process. Syst., vol. 38, no. 2, pp. 147- 156, 2004.
[13] J. Daugman, "New Methods in Iris Recognition," IEEE Transaction on Systems, Man and Cybernatics-Part B: Cybernatics, vol. 37, pp. 1167- 1175, October 2007.
[14] J. Canny, "A computational approach to edge detection," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 8, no. 6, pp. 679-698, 1986.
[15] M. Vasta, R. Singh, and A.Noore, "Reducing the False Rejection Rate of Iris Recognition Using Textural and Topological Fearures," International Journal of Signal Processing, vol. 2, no. 2, pp. 66-72, 2005.
[16] A. Jensen and A. la Cour-Harbo, Ripples in Mathematics: The Discrete Wavelet Transform. Springer, 2001.
[17] P. Th'evenaz, T. Blu, and M. Unser, "Interpolation revisited," IEEE Transactions on Medical Imaging, vol. 19, pp. 739-758, July 2000.
[18] R. C. Gonzalez and R. E. Woods, Digital Image Processing. Prentice Hall, 2nd ed., 2002.
[19] "University of Bath iris image database, 2007." http://www.bath.ac.uk/elec-eng/research/sipg/irisw (accessed July, 2007).
[20] H. Proenc┬©a and L. A. Alexandre, "Ubiris: A noisy iris image database.," in ICIAP (F. Roli and S. Vitulano, eds.), vol. 3617 of Lecture Notes in Computer Science, pp. 970-977, Springer, 2005.
[21] "Multimedia University iris image database." http://pesona.mmu.edu.my/˜ccteo/ (accessed July, 2007).
[22] "CASIA iris image database." http://www.sinobiometrics.com (accessed July, 2007).
[23] "Iris Challenge Evaluation,2005." http://iris.nist.gov/ice/ (accessed July, 2008), 2005.
[24] L. Ma, T. Tan, D. Zhang, and Y. Wang, "Local Intensity Variation Analysis for Iris Recognition," Pattern Recognition, vol. 37, no. 6, pp. 1287-1298, 2004.