Robust and Accurate Iris Segmentation Algorithm for Color and Noisy Eye Images

Authors

DOI:

https://doi.org/10.26636/jtit.2010.4.1090

Keywords:

biometrics, image segmentation, iris recognition

Abstract

Efficient and robust segmentation of iris images captured in the uncontrolled environments is one of the challenges of non-cooperative iris recognition systems. We address this problem by proposing a novel iris segmentation algorithm, which is suitable both for monochrome and color eye images. The method presented use modified Hough transform to roughly localize the possible iris and pupil boundaries, approximating them by circles. A voting mechanisms is applied to select a candidate iris regions. The detailed iris boundary is approximated by the spline curve. Its shape is determined by minimizing introduced boundary energy function. The described algorithm was submitted to the NICE.I iris image segmentation contest, when it was ranked 11th and 10th out of total 97.

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References

[1] H. Proença and L. A. Alexandre, „The NICE.I: noisy iris challenge evaluation, part I”, in Proc. Int. Conf. Biometr. Theory, Appl. Sys., Washington, USA, 2007, pp. 1-4.
View in Google Scholar

[2] H. Proença and L. A. Alexandre, „UBIRIS: a noisy iris image database”, Lect. Notes Comput. Sci., vol. 3617, pp. 970-977, 2005 [Online]. Available: http://iris.di.ubi.pt
View in Google Scholar

[3] T. Tan, Z. He, and Z. Sun, „Efficient and robust segmentation of noisy iris images for non-cooperative iris recognition”, Image Vision Comput., vol. 28, pp. 223-230, 2010.
View in Google Scholar

[4] M. A. Luengo-Oroz, E. Faure, and J. Angulo, „Robust iris segmentation on uncalibrated noisy images using mathematical morphology”, Image Vision Comput., vol. 28, pp. 278-284, 2010.
View in Google Scholar

[5] Y. Chen et al., „A highly accurate and computationally efficient approach for unconstrained iris segmentation”, Image and Vision Comput., vol. 28, pp. 261-269, 2010.
View in Google Scholar

[6] W. Sankowski, K. Grabowski, M. Napieralska, M. Zubert, and A. Napieralski, „Reliable algorithm for iris segmentation in eye image”, Image Vision Comput., vol. 28, pp. 231-237, 2010.
View in Google Scholar

[7] P. de Almeida, „A knowledge-based approach to the iris segmentation problem”, Image Vision Comput., vol. 28, pp. 238-245, 2010.
View in Google Scholar

[8] P. Li, X. Liu, L. Xiao, and Q. Song, „Robust and accurate iris segmentation in very noisy iris images”, Image Vision Comput., vol. 28, pp. 246-253, 2010.
View in Google Scholar

[9] D. S. Jeong et al., „A new iris segmentation method for non-ideal iris images”, Image Vision Comput., vol. 28, pp. 254-260, 2010.
View in Google Scholar

[10] R. D. Labati and F. Scotti, „Noisy iris segmentation with boundary regularization and reflections removal”, Image Vision Comput., vol. 28, pp. 270-277, 2010.
View in Google Scholar

[11] J. Daugman, „New methods in iris recognition”, IEEE Trans. Sys. Man Cyb., Part B, Cybernetics, vol. 37, no. 5, pp. 1167-1175, 2007.
View in Google Scholar

[12] J. Daugman, „How iris recognition works?”, IEEE Trans. Circ. Sys. Video Technol., vol. 14, no. 1, pp. 21-30, 2004.
View in Google Scholar

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Submitted

2023-06-27

Published

2010-12-30

Issue

Section

RESEARCH ARTICLES

How to Cite

[1]
P. Strzelczyk, “ Robust and Accurate Iris Segmentation Algorithm for Color and Noisy Eye Images”, JTIT, vol. 42, no. 4, pp. 5–9, Dec. 2010, doi: 10.26636/jtit.2010.4.1090.

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