{"title":"Multi-algorithmic Iris Authentication System","authors":"Hunny Mehrotra, Banshidhar Majhi, Phalguni Gupta","volume":20,"journal":"International Journal of Computer and Information Engineering","pagesStart":2575,"pagesEnd":2580,"ISSN":"1307-6892","URL":"https:\/\/publications.waset.org\/pdf\/3350","abstract":"The paper proposes a novel technique for iris\r\nrecognition using texture and phase features. Texture features are\r\nextracted on the normalized iris strip using Haar Wavelet while phase\r\nfeatures are obtained using LOG Gabor Wavelet. The matching\r\nscores generated from individual modules are combined using sum of\r\nscore technique. The system is tested on database obtained from Bath\r\nUniversity and Indian Institute of Technology Kanpur and is giving\r\nan accuracy of 95.62% and 97.66% respectively. The FAR and FRR\r\nof the combined system is also reduced comparatively.","references":"[1] L. Flom, and A. Safir, \"Iris Recognition System,\" U.S Patent No.\r\n4641349. U.S Government Printing Office, Washington DC, 1987.\r\n[2] J. Daugman, \"Biometric Personal Identification System Based on Iris\r\nAnalysis,\" US patent 5291560, Patent and Trademark Office,\r\nWashington, D.C., 1994.\r\n[3] L. Ma, T. Tan, Y. Wang, and D. Zhang, \"Personal identification based\r\non iris texture analysis,\" In IEEE Pattern Analysis and Machine\r\nIntelligence, volume 25, pp. 1519-1533, 2003.\r\n[4] C. Kimme, D. Ballard, and J. Sklansky, \"Finding circles by an array of\r\naccumulators,\" ACM Commununication, volume 18(2), pp. 120-122,\r\n1975.\r\n[5] M. Rizon, H. Yazid, P. Saad, A. Y. Md. Shakaff, A. S. Rahman, M.\r\nSugisaka, S. Yaacob, M. M. Rozailan, and M. Karthigayan, \"Object\r\ndetection using circular hough transform,\" American Journal of Applied\r\nSciences, volume 2(12), 2005.\r\n[6] S. Lim, K. Lee, O. Byeon, and T. Kim, \"Efficient iris recognition\r\nthrough improvement of feature vector and classifier,\" ETRI journal,\r\nvolume 23(2), pp. 61-70, 2001.\r\n[7] D. J. Field, \"Relations between the statistics of natural images and the\r\nresponse properties of cortical cells,\" J. Opt. Soc. Am. A, volume 4(12),\r\npp. 23-79, 1987.\r\n[8] J. Daugman, \"Statistical Richness of Visual Phase Information: Update\r\non Recognizing Persons by Iris Patterns,\" International Journal on\r\nComputer Vision, volume 45(1), pp. 25-38, 2001.\r\n[9] Y. Zhu, T. Tan, and Y. Wang, \"Biometric personal identification based\r\non iris patterns,\" Proceedings of 15th International Conference on\r\nPattern Recognition, volume 2, pp. 801-804, 2000.\r\n[10] W. W. Boles, and B. Boashash, \"A human identification technique using\r\nimages of the iris and wavelet transform,\" IEEE Transactions on Signal\r\nProcessing, volume 46(4), pp. 1185-1188, 1998.\r\n[11] L. Ma, T. Tan, Y. Wang, and D. Zhang, \"Local intensity variation\r\nanalysis for iris recognition,\" Pattern Recognition, volume 37(6), pp.\r\n1287-1298, 2004.\r\n[12] L. Masek, \"Recognition of Human Iris Patterns for Biometrics\r\nIdentification,\" B.Eng's thesis, University of Western Australia, 2003.\r\n[13] http:\/\/www.bath.ac.uk\/elec-eng\/research\/sipg\/irisweb\/database.htm\r\n[14] J. Daugman, \"The importance of being random: Statistical principles of\r\niris recognition,\" Pattern Recognition, volume 36(2), pp. 279-291, 2003.","publisher":"World Academy of Science, Engineering and Technology","index":"Open Science Index 20, 2008"}