Abstract
Although iris recognition technology has been reported to be more stable and reliable than other biometric systems, performance can be degraded due to many factors such as small eyes, camera defocusing, eyelash occlusions and specular reflections on the surface of glasses. In this paper, we propose a new multi-unit iris authentication method that uses score level fusion based on a support vector machine (SVM) and a quality assessment method for mobile phones. Compared to previous research, this paper presents the following two contributions. First, we reduced the false rejection rate and improved iris recognition accuracy by using iris quality assessment. Second, if even two iris images were determined to be of bad quality, we captured the iris images again without using a recognition process. If only one iris image among the left and right irises was regarded as a good one, it was used for recognition. However, if both the left and right iris images were good, we performed multi-unit iris recognition using score level fusion based on a SVM. Experimental results showed that the accuracy of the proposed method was superior to previous methods that used only one good iris image or those methods that used conventional fusion methods.
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Ratha, N.K., Govindaraju, V.: Advances in Biometrics—Sensors, Algorithms and Systems. Springer, Heidelberg (2007)
Bolle, R.M., Connell, J.H., Pankanti, S., Ratha, N.K., Senior, A.W.: Guide to Biometrics. Springer, Heidelberg (2003)
Hallinan, P.W.: Recognizing human eyes. Geometric Methods Comput. Vis. 1570, 214–226 (1991)
Ross, A., Jain, A., Qian, J.Z.: Information fusion in biometrics. Pattern Recognit. Lett. 24(13), 2115–2125 (2003)
Jain, J., Son, J., Lee, Y., Park, K.R.: Multi-unit iris recognition system by image check algorithm. In: Lecture Notes in Computer Science on ICBA2004, vol. 3072, pp. 450–457 (2004)
BM-ET 200: http://www.panasonic.com/business/security/biometrics.asp. Accessed 20 October 2008
IrisAccess 4000: http://www.lgiris.com/ps/products/index.htm. Accessed 20 October 2008
IrisPass-M: http://www.oki.com/jp/FSC/iris/en/index.html. Accessed 20 October 2008
Park K.R., Park H.A., Kang B.J., Lee E.C., Jeong D.S.: A study on iris localization and recognition on mobile phone. Eur. J. Adv. Signal Process. 2008(281943), 1–12 (2008)
Forrester J., Dick A., McMenamin P., Lee W.: The Eye: Basic Sciences in Practice. W. B. Saunders, London (2001)
Shih, S.W. et al.: A novel approach to 3-D gaze tracking using stereo cameras. IEEE Trans. Syst. Man Cybern. Part B 34(1), 234–245 (2004)
Park, H.A., Park, K.R.: Iris recognition based on score level fusion by using SVM. Pattern Recognit. Lett. 28(15), 2019–2028 (2007)
Daugman, J.G.: High confidence visual recognition of persons by a test of statistical independence. IEEE Trans. Pattern Anal. Mach. Intell. 15(11), 1148–1161 (1993)
Daugman, J.G.: How iris recognition works. IEEE Trans. Circ. Syst. Video Technol. 14(1), 21–29 (2004)
CASIA Iris Database: http://www.cbsr.ia.ac.cn/english/Databases.asp. Accessed 20 October 2008
Chen, Y. et al.: Localized iris image quality using 2-D wavelets. In: Lecture Notes in Computer Science on ICB, vol. 3832, pp. 373–381 (2006)
Zhoushi, W. et al.: Robust and fast assessment of iris image quality. In: Lecture Notes in Computer Science on ICB, vol. 3832, pp. 464–471 (2006)
Cho, D. et al.: Pupil and Iris Localization for Iris Recognition in Mobile Phones. SNPD, Las Vegas Nevada, June 19–20 (2006)
Krichen, E. et al.: Color-based iris verification. In: LNCS on ICB07, vol. 4642, pp. 997–1005 (2007)
Wildes, R.: Automated iris recognition: an emerging biometric technology. Proc. IEEE 85(9), 1348–1363 (1997)
Masek, L., Kovesi, P.: MATLAB Source Code for a Biometric Identification System Based on Iris Patterns, The School of Computer Science and Software Engineering, The University of WesternAustralia (2003)
Kalka, N.D. et al.: Image quality assessment for iris biometric. In: Proceedings of SPIE Conference on Biometric Technology for Human Identification III, vol. 6202, pp. 61020D-1–6202D-11 (2006)
Kang, B.J., Park, K.R.: Restoration of motion-blurred iris image on mobile iris recognition devices. Opt. Eng. 47(11), 117202-1–117202-8 (2008)
Jang Y.K. et al.: Robust eyelid detection for iris recognition. J. IEEK 44(1), 94–104 (2007)
Kang, B.J., Park, K.R.: A robust eyelash detection based on iris focus assessment. Pattern Recognit. Lett. 28(15), 1630–1639 (2007)
Kang, B.J., Park, K.R.: A study on iris image restoration. In: Lecture Notes in Computer Science on AVBPA 2005, vol. 3546, pp. 31–40 (2005)
Duda R.O., Hart P.E., Stork D.G.: Pattern Classification. Wiley, New York (2001)
Jang, J., Park, K.R.,Kim, J., Lee,Y.:Newfocus assessment method for iris recognition systems. Pattern Recognit. Lett. 29(13), 1759–1767 (2008)
Ben-Yacoub, S.: Multi-modal data fusion for person authentication using SVM. In: Proceedings of International Conference on Audio and Video based Person Authentication, pp. 25–30 (1999)
Wang, Y., Han, J.: Iris recognition using support vector machines. In: Lecture Notes in Computer Science on ISNN 2004, pp. 622–628 (2004)
Gu, H., Gao, Z., Wu, F.: Selection of optimal features for iris recognition. In: Advances in Neural Networks-ISNN 2005, vol. 3479, p. 81 (2005)
Roy, K., Bhattacharya, P.: Iris recognition with support vector machines. In: LNCS on ICB06, vol. 3832, pp. 486–492 (2006)
Vapnik, V.: Statistical Learning Theory. Wiley, NY (1998)
Schölkopf, B., Williamson, R.C., Smola, A.J., Shawe-Taylor, J.: In: Solla, S., Leen, T., Müller, K.-R. (eds.), Neural Information Systems, vol. 12, MIT Press, USA (2000)
Samsung SCH-V770: http://www.anycall.com. Accessed 20 October 2008
Daugman, J.G.: Newmethods in iris recognition. IEEE Trans. Syst. Man Cybern. 37(5), 1167–1175 (2007)
Effect of Severe Image Compression on Iris RecognitionPerformance: http://www.cl.cam.ac.uk/techreports/UCAM-CL-TR-685.pdf. Accessed 20 October 2008
Phillips, P.J., Bowyer, K.W., Flynn, P.J.: Comments on the CASIA Version 1.0 Iris Data Set. IEEE Trans. Pattern Anal. Mach. Intell. 29(10), 1869–1870 (2007)
Yamane, T.: Statistics, in An Introductory Analysis. 2nd edn. Harper & Row, New York (1967)
ARM Cortex-A8 Processor: http://www.arm.com/products/CPUs/ARM_Cortex-A8.html. Accessed 20 October 2008
Samsung mobile phone (i8510) with 8 M Pixel camera: http://www.gsmarena.com/8_mp_samsung_i8510_primera_surfaces_has_it_all_but_the_kitchen_sink-news-546.php. Accessed 20 October 2008
LG Electronics: http://www.lge.com. Accessed 20 October 2008
Pantech: http://www.pantech.com. Accessed 20 October 2008
Matey, J.R., Ackerman, D., Bergen, J., Tinker, M.: Iris recognition in less constrained environments. In: Advances in Biometrics, Springer, Heidelberg, pp. 107–131 (2008)
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Kang, B.J., Park, K.R. A new multi-unit iris authentication based on quality assessment and score level fusion for mobile phones. Machine Vision and Applications 21, 541–553 (2010). https://doi.org/10.1007/s00138-009-0184-0
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DOI: https://doi.org/10.1007/s00138-009-0184-0