Iris Authentication Using PSO

International Journal of Computer & Organization Trends (IJCOT)          
© 2012 by IJCOT Journal
Volume-2 Issue-1                           
Year of Publication : 2012
Authors : Mr. Logannathan.B, Dr. Marimuthu. 


Mr. Logannathan.B, Dr. Marimuthu. "Iris Authentication Using PSO" . International Journal of Computer & organization Trends (IJCOT), V2(1):1-5 Jan - Feb 2012, Published by Seventh Sense Research Group.


The paper proposes a wavelet probabilistic neural network (WPNN) for iris biometric classifier. The WPNN combines wavelet neural network and probabilistic neural network for a new classifier model which will be able to improve the biometrics recognition accuracy as well as the global system performance. A simple and fast training algorithm, particle swarm optimization (PSO), is also introduced for training the wavelet probabilistic neural network. In iris matching, the CASIA iris database is used and the experimental results show that the feasibility and performance of the proposed method.


[1] P.W. Hallinan “Recognizing Human Eyes,” Geometric Methods Comput. Vision. Vol. 1570, pp. 214-226, 1991.
[2] J. Daugman, Biometric Personal Identification System Based on Iris Analysis, United States Patent, no. 5291560, 1994
[3] J.Daugman,“High Confidence Visual Recognition of Person by a Test of Statistical Independence,” IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 15, no. 11, pp1148-1151, Nov. 1993
[4] J. Daugman, “Demodulation by Complex-Valued Wavelets for Stochastic Pattern Recognition,” Int’l J, Wavelets, Multiresolution and Information Processing, vol. 1, no. 1, pp. 1-17, 2003.
[5] J. Daugman, “Statistical Richness of Visual Phase Information: Update on Recognition Persons by Iris Patterns,” Int’l J. Computer Vision, vol. 45, no. 1, pp. 25-38 2001.
[6] Li Ma, Tieniu Tan, Yunhong Wng, and Dexin Zhang, “ Personal Identification Based on Iris Texture Analysis”, IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 25, no. 12, pp. 1519-1532, Dec. 2003
[7] C. Sidney Burrus Ramesh A.Gopinath Hai ta Guo, “Introduction to Wavelets and Wavelet Transforms: A Primer”, 1998.
[8] R.Wildes, J.Asmuth, G. Green, S. Hsu, R. Kolczynski, J. Matey, and S. McBride, “A Machine-Vision System for Iris Recognition,” Machine Vision and Application, vol. 9, pp. 1-8, 1996.
[9]R.Wildes,“Iris Recognition: An Emerging Biometric Technology,” Proc. IEEE, vol. 85, pp. 1348-1363, 1997.
[10] W. Boles and B. Boashash, “ A Human Identification Technique Using Images of the Iris and Wavelet Transform,” IEEE Trans. Signal Processing, vol. 46, no. 4, pp. 1185-1188, 1998.
[11] L. Ma, Y. Wang, T. Tan“Iris Recognition Based on Multichannel Gabor Filtering”, Processing of ACCV’ 2002, vol.1, pp. 279-283, 2002.
[12]Ching-Han CHEN, Chia-Te CHU,"High Efficiency Iris Feature Extraction Based on 1-D Wavelet Transform ", Int. Computer Symposium, Taipei, pp. 1012-1017, 2004
[13] Jaideva C.Goswami and Andrew K. Chan “Fundamentals of Wavelets” 1999.
[14]A.Rosenfeld, A.C. Kak, Digital Picture Processing, Academic Press, New York, 1976.
[15] D.F.Specht,”Probabilistic Neural Network for Classification, Map, or Associative Memory”, Proceeding of the IEEE International Conference on Neural Network, vol.1, pp525-532, 1988.
[16] CASIA iris database. Institute of Automation, Chinese Academy of Sciences,
[17] Ching-Han CHEN and CHIA-Te CHU,”High Efficiency Feature Extraction Based on 1-D Wavelet Transform for RealTime Face Recognition”, WSEAS Trans. on Information Science & Applications. Issue 1, Vol. 1, pp.411-417, July 2004.
[18]J.Kennedy et al. ,"Particle Swarm Optimization", Proc of IEEE Int. Conf. Neural Networks, vol. IV, pp.1942-1948, 1995.
[19] Y.shi and R.C.Eberthart, "A Modified Particle Swarm Optimizer", IEEE Int. Conf. Evolutionary Computation, May, 1998.
[20]Q.Zhang and A. Benveniste, "Wavelet Networks", IEEE Trans. Neural Net. , vol.3, pp.889-898, Nov 1992.
[21] Jian-Guo Zheng, Ping-Ping Song, "Use of Immune Selfadaptation Wavelet for Data Mining", Proc. of 1th Int’ Conf. on Machine Learning and Cybernetics., pp.156-160, Beijing, China, Nov 4-5. 2002.
[22] V.Kruger and G.Sommer, "Affine Real-Time Face Tracking Using a Wavelet Network", ICCV’99 Workshop Recognition, Analysis, and Tracking of Faces and Gestures in Real-Time Systems. Corfu, Greece, Sep.1999.
[23] Roberto K. H. Galvao and Takashi Yoneyama, "A Competitive Wavelet Network for Signal Clustering", IEEE Trans. Systems. Man Cybernetics., vol. 34, no. 2, pp.1282-1288, April. 2004.