Abstract
Recent researches on iris recognition without user cooperation have introduced video-based iris capturing approach. Indeed, it provides more information and more flexibility in the image acquisition stage for noncooperative iris recognition systems. However, a video sequence can contain images with different level of quality. Therefore, it is necessary to select the highest quality images from each video to improve iris recognition performance. In this paper, we propose as part of a video quality assessment module, a new local quality iris image method based on spectral energy analysis. This approach does not require the iris region segmentation to determine the quality of the image such as most of existing approaches. In contrast to other methods, the proposed algorithm uses a significant portion of the iris region to measure the quality in that area. This method evaluates the energy of 1000 images which were extracted from 200 iris videos from the MBGC NIR video database. The results show that the proposed method is very effective to assess the quality of the iris information. It obtains the highest 2 images energies as the best 2 images from each video in 226 milliseconds.
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Kang, B.J., Park, K.R.: A study on fast iris restoration based on focus checking. In: Perales, F.J., Fisher, R.B. (eds.) AMDO 2006. LNCS, vol. 4069, pp. 19–28. Springer, Heidelberg (2006)
Zamudio-Fuentes, L.M., García-Vázquez, M.S., Ramírez-Acosta, A.A.: Iris Segmentation Using a Statistical Approach. In: Martínez-Trinidad, J.F., Carrasco-Ochoa, J.A., Kittler, J. (eds.) MCPR 2010. LNCS, vol. 6256, pp. 164–170. Springer, Heidelberg (2010)
García-Vázquez, M., Ramírez-Acosta, A.: Person verification process using iris information. Research in Computing Science 44, 97–104 (2009)
Zamudio, L.M.: Reconocimiento del iris como identificación biométrica utilizando el video. MSc thesis, IPN (January 2011)
Chen, Y., Dass, S.C., Jain, A.K.: Localized iris image quality using 2-d wavelets. In: ICB 2006 (2006)
Huang, Y., Ma, Z., Xie, M.: Rapid and effective method of quality assessment on sequence iris image. In: MIPPR 2007. Proc. of SPIE, vol. 6786 (2007)
Colores-Vargas, J.M., García-Vázquez, M.S., Ramírez-Acosta, A.A.: Measurement of defocus level in iris images using different convolution kernel methods. In: Martínez-Trinidad, J.F., Carrasco-Ochoa, J.A., Kittler, J. (eds.) MCPR 2010. LNCS, vol. 6256, pp. 125–133. Springer, Heidelberg (2010)
Kang, B.J., Park, K.R.: Real-time image restoration for iris recognition Systems. IEEE Trans. on Systems 37(6), 1555–1566 (2007)
Kang, B.J., Park, K.R.: A study on restoration of iris images with motion-and-optical blur on mobile iris recognition devices. Wiley Periodicals (2009)
Lee, Y., Phillips, P.J., Micheals, R.J.: An Automated Video-Based System for Iris Recognition. In: Tistarelli, M., Nixon, M.S. (eds.) ICB 2009. LNCS, vol. 5558, pp. 1160–1169. Springer, Heidelberg (2009)
Daugman, J.G.: How iris recognition works. IEEE Trans. Circ. Syst. Video Tech. 14(1), 21–30 (2004)
Gonzalez, R.C., Woods, R.: Digital image processing. Addison-Wesley (1996)
Correlation and Spectral Density, http://www.ensc.sfu.ca/~jiel/courses/327/bin/pdf/Pre_15_Rxx.pdf
Multi Biometric Grand Challenge, http://face.nist.gov/mbgc
Image formation, http://www.cs.toronto.edu/~fleet/courses/2503/fall10/Handouts/imageFormation.pdf
Chinese Academy of Sciences, Institute of Automation (CASIA), http://figment.cse.usf.edu/~sfefilat/data/papers/WeBCT9.29.pdf
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Zamudio-Fuentes, L.M., García-Vázquez, M.S., Ramírez-Acosta, A.A. (2011). Local Quality Method for the Iris Image Pattern. In: San Martin, C., Kim, SW. (eds) Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications. CIARP 2011. Lecture Notes in Computer Science, vol 7042. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-25085-9_9
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DOI: https://doi.org/10.1007/978-3-642-25085-9_9
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