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Multi-algorithmic IRIS Recognition
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 38 - Number 11 |
| Year of Publication: 2012 |
| Authors: G. Sathish, Dr. S.V.Saravanan, Dr. S. Narmadha, Dr. S. Uma Maheswari |
10.5120/4745-6934
|
G. Sathish, Dr. S.V.Saravanan, Dr. S. Narmadha, Dr. S. Uma Maheswari . Multi-algorithmic IRIS Recognition. International Journal of Computer Applications. 38, 11 ( January 2012), 13-21. DOI=10.5120/4745-6934
Abstract
Modern societies give higher relevance to personal recognition system that contribute to the increase of security and reliability, essentially due to terrorism and other extremism or illegal activities. The objective of this work is to present a multi-algorithmic biometric authentication system for physical access control based on iris pattern for high security access. The CASIA database of IRIS images provided by Chinese Academy of Sciences Institute of Automation is used and the system is implemented in MATLAB. The iris recognition is based on Daugman's approach and multiple classifiers using Hamming distance and Neural networks. In Daugman's approach, the iris features are extracted using 2D Gabor Wavelets. The proposed work provides match for iris pattern if hamming distance is below 0.15 whereas for the existing works it is 0.20. The Neural Classifier uses a feed forward network with three hidden layers and used after normalization and feature extraction phase. Features given to neural network are Energy, Entropy, Standard deviation, Covariance. The error rate has been reduced from e-3 to e-5 in this proposed work. The multi-algorithmic approach together with improvement in segmentation and matching stages is found to report higher verification accuracy with lower error rate.
References
- Anil Ross and Anil K. Jain. 2004. Multimodal Biometrics: An Overview, Proceedings of 12th European Signal Processing Conference, pp. 1221 - 1224.
- Pentland A., Mogghadam B. and Starner T. 2004. View-based and Modular Eigen spaces for Face Recognition, Proceedings of Computer vision and Pattern Recognition, pp. 84-91.
- Bertillon, A. 1885. La couleur de Piris, Revue scientifique, Vol. 36, No. 3, pp. 65-73.
- Daugman, J. 1992. High confidence personal identification by rapid video analysis of iris texture, Proc. of the IEEE, International Carnahan Conf. on Security Technology.
- Flom, L. and Safir, A. 1987. Iris Recognition System, U.S Patent No.4641349. U.S Government Printing Office, Washington DC.
- Daugman J., 1985. Uncertainty Relation for Resolution in Space, Spatial Frequency and Orientation Optimized by Two Dimensional Visual Cortical Filters, Proceedings of International Conference on Pattern Recognition, pp. 1160-1169.
- Daugman J., 1993. High Confidence Visual Recognition of persons by a Test of Statistical Independence, IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 15, No. 11, pp. 1148-1161.
- Daugman J. 2001. Statistical Richness of Visual Phase Information: Update on Recognizing Persons by Iris Patterns, International Journal on Computer Vision, Vol. 45, No. 1, pp. 25-38.
- Boles, W.W. and Boashash, B. 1998. A Human Identification Technique using Images of the Iris and Wavelet Transform, IEEE Transactions on Signal Processing, Vol. 46, No. 4, pp. 1185-1188.
- Wildes, R.P., Asmuth, J.C., Green, G.L., Hsu S.C., Kolcynski R.J., Matey J.R and Mcbride S.E. 1996. A Machine-Vision System for Iris recognition, Journal on Machine Vision and Applications, Vol. 9, pp. 1-8.
- Lim S., Lee K., Byeon O., and Kim T. 2001. Efficient Iris Recognition through improvement of Feature Vector and Classifier, Journal on Electronics and Telecommunications Research Institute, Vol. 23, No. 2, pp. 61-70.
- Daugman J. 1994. Biometric Personal Identification System Based on Iris Analysis, US Patent 5291560, Patent and Trademark Office, Washington, D.C., 1994.
- Zhu Y., Tan T., and Wang Y. 2000. Biometric Personal Identification Based on Iris Patterns, Proceedings of the 15th International Conference on Pattern Recognition, Spain, Vol. 2, pp. 1519-1533.
- Qussay A. Salih and Vinod Dhandapani. 2006. Iris Recognition based on Multi-Channel Feature Extraction using Gabor Filters, Proceedings of the Lasted International Conference, Advances in Science and Technology, Mexico.
- Uma Maheswari S., Anbalagan P. and Priya T. 2008 Efficient Iris Recognition through Improvement in Iris Segmentation Algorithm, International Journal on Graphics, Vision and Image Processing (GVIP), Vol. 8, No. 2, pp. 29 - 35.
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