Abstract
Blurred iris images are inevitable during iris image acquisition due to limited depth of field and movement of subjects. The blurred iris images lose detailed texture information for accurate identity verification, so this paper proposes a novel iris image deblurring method to enhance the quality of blurred iris images. Our method makes full use of the prior information of iris images. Firstly, benefiting from the properties of iris images, a set of initialization methods for point spread function (PSF) is proposed to obtain a better start point than that of common deblurring methods. Secondly, only the most reliable iris image regions which are obtained by structure properties of iris images are used to refine the initial PSF. Finally, the more accurate PSF is used to reconstruct the clear iris texture for higher accuracy of iris recognition. Experimental results on both synthetic and real-world iris images illustrate that the proposed method is effective and efficient, and outperforms state-of-the-art iris image deblurring methods in terms of the improvement of iris recognition accuracy.
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References
Fergus, R., Singh, B., Hertzmann, A., Roweis, S., Freeman, W.: Removing camera shake from a single photograph. ACM Trans. on Graphics 25, 787–794 (2006)
Kang, B., Park, K.: Real-time image restoration for iris recognition systems. IEEE Trans. on Systems, Man, and Cybernetics, Part B: Cybernetics 37, 1555–1566 (2007)
Huang, X., Ren, L., Yang, R.: Image deblurring for less intrusive iris capture. In: IEEE Conf. on Computer Vision and Pattern Recognition, pp. 1558–1565. IEEE (2009)
Kang, B., Park, K.: Restoration of motion-blurred iris images on mobile iris recognition devices. Optical Engineering 47, 117202 (2008)
Cho, S., Lee, S.: Fast motion deblurring. In: ACM Trans. on Graphics, vol. 28, p. 145 (2009)
Shan, Q., Jia, J., Agarwala, A.: High-quality motion deblurring from a single image. In: ACM Trans. on Graphics, vol. 27, p. 73. ACM (2008)
Sun, Z., Tan, T.: Ordinal measures for iris recognition. IEEE Trans. on Pattern Analysis and Machine Intelligence, 2211–2226 (2009)
Wei, Z., Tan, T., Sun, Z., Cui, J.: Robust and fast assessment of iris image quality. Advances in Biometrics, 464–471 (2005)
Daugman, J.: How iris recognition works. IEEE Trans. on Circuits and Systems for Video Technology 14, 21–30 (2004)
Daugman, J.: High confidence visual recognition of persons by a test of statistical independence. IEEE Trans. on Pattern Analysis and Machine Intelligence 15, 1148–1161 (1993)
He, Z., Tan, T., Sun, Z., Qiu, X.: Toward accurate and fast iris segmentation for iris biometrics. IEEE Trans. on Pattern Analysis and Machine Intelligence 31, 1670–1684 (2009)
Levin, A., Weiss, Y., Durand, F., Freeman, W.: Understanding and evaluating blind deconvolution algorithms. In: IEEE Conf. on Computer Vision and Pattern Recognition, pp. 1964–1971. IEEE (2009)
Xu, L., Jia, J.: Two-Phase Kernel Estimation for Robust Motion Deblurring. In: Daniilidis, K., Maragos, P., Paragios, N. (eds.) ECCV 2010, Part I. LNCS, vol. 6311, pp. 157–170. Springer, Heidelberg (2010)
Krishnan, D., Tay, T., Fergus, R.: Blind deconvolution using a normalized sparsity measure. In: IEEE Conf. on Computer Vision and Pattern Recognition, pp. 233–240. IEEE (2011)
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Liu, J., Sun, Z., Tan, T. (2012). Iris Image Deblurring Based on Refinement of Point Spread Function. In: Zheng, WS., Sun, Z., Wang, Y., Chen, X., Yuen, P.C., Lai, J. (eds) Biometric Recognition. CCBR 2012. Lecture Notes in Computer Science, vol 7701. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-35136-5_23
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DOI: https://doi.org/10.1007/978-3-642-35136-5_23
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