Abstract
Despite the rapid development of iris image capturing system and recognition algorithms, defocused iris images occurs a lot due to the restriction of optical system’s depth of field. To take advantage of the useful texture information for iris recognition in more unconstrained environment, we proposed a scheme for iris image deblurring based on fitting ellipse curve in the frequency spectral image. To get the parameters for Point Spread Function(PSF) initialization, we first calculate the frequency spectral image of defocused iris images, and then fit the ellipse with Hough Transform to get the defocus estimation. Blind deconvolution is chosen as the restoration method in which the PSF is refined through iteration. Experiments with both artificial data and real data are conducted and the results demonstrated the effectiveness of our method to restore defocused iris images.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Stoker, D., Wedd, J., Lavelle, E., Laan, J.: Restoration and recognition of distant, blurry irises. Applied Optics 52(9), 1864–1875 (2013)
Kang, B., Park, R.: A Study on Restoration of Iris Images with Motion-and-Optical Blur on Mobile Iris Recognition Devices. J. International Journal of Imaging Systems and Technology 19, 323–331 (2009)
Liu, B., Lam, S., Srikanthan, T., Yuan, W.: Iris Recognition of Defocused Images for Mobile Phones. J. International Journal of Pattern Recognition and Artificial Intelligence 26(8), 1260010-1–1260010-23 (2012)
Sazonova, N., Schuckers, S., Johnson, P., Lopez, P., Sazonov, E.: Impact of out-of-focus blur on iris recognition. In: Proceedings of the SPIE-The International Society for Optical Engineering, p. 80291S. SPIE Press, Florida (2011)
Nguyen, K., Fookes, C., Sridharan, S., Denman, S.: Focus-score Weighted Super-resolution for Uncooperative Iris Recognition at a Distance and on The Move. In: 2010 25th International Conference of Image and Vision Computing New Zealand (IVCNZ), pp. 1–8. IEEE Press, Queenstown (2010)
Liu, J., Sun, Z., Tan, T.: Iris image deblurring based on refinement of point spread function. In: Zheng, W.-S., Sun, Z., Wang, Y., Chen, X., Yuen, P.C., Lai, J. (eds.) CCBR 2012. LNCS, vol. 7701, pp. 184–192. Springer, Heidelberg (2012)
Kang, B., Park, K.: Real-time image restoration for iris recognition systems. IEEE Trans. on Systems, Man, and Cybernetics, Part B 37, 1555–1566 (2007)
Kang, B., Park, K.: Restoration of motion-blurred iris image on mobile iris recognition devices. Optical Engineering 47, 117202-1–117202-8 (2008)
Basca, C.A., Talos, M., Brad, R.: Randomized Hough Transform for Ellipse Detection with Result Clustering, Computer as a Tool. In: EUROCON 2005, vol. 2, pp. 1397–1400 (2005)
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)
Daugman, J.: How iris recognition works. IEEE Trans. on Circuits and Systems for Video Technology 14, 21–30 (2004)
Ma, L., Wang, Y., Tan, T.: Iris Recognition Based on Multichannel Gabor Filtering. In: Asian Conference on Computer Vision, pp. 279–283. ACCV Press, Melbourne (2002)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2013 Springer International Publishing Switzerland
About this paper
Cite this paper
Ren, H., He, Y., Wang, S., Gan, C., Wang, J. (2013). Defocused Iris Image Restoration Based on Spectral Curve Fitting. In: Sun, Z., Shan, S., Yang, G., Zhou, J., Wang, Y., Yin, Y. (eds) Biometric Recognition. CCBR 2013. Lecture Notes in Computer Science, vol 8232. Springer, Cham. https://doi.org/10.1007/978-3-319-02961-0_42
Download citation
DOI: https://doi.org/10.1007/978-3-319-02961-0_42
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-02960-3
Online ISBN: 978-3-319-02961-0
eBook Packages: Computer ScienceComputer Science (R0)