文章基本信息

标题：EFFECT OF DIFFERENT NEURAL NETWORKS ON THE ACCURACY IN IRIS PATTERNS RECOGNITION
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作者：M. GOPIKRISHNAN ; Dr. T. SANTHANAM
期刊名称：International Journal of Reviews in Computing
印刷版ISSN：2076-3328
电子版ISSN：2076-3336
出版年度：2011
卷号：7
页码：22-28
出版社：Little Lion Scientific Research and Developement
摘要：A biometric system provides automatic identification of an individual based on a unique feature or characteristic possessed by the individual. Iris recognition is regarded as the most reliable and accurate biometric identification system available. An approach for accurate Biometric Recognition and identification of Human Iris Patterns using Neural Network has been illustrated by gopikrishnan.m etal. In this paper, based on the accurate methodology suggested by gopikrishnan.m etal, we extend the work for optimization for Iris Patterns recognition using two neural network models for comparing the performance. The results from the Cascade forward back propagation neural model and Feed forward back propagation network model have been found to be better than the results presented in the literature using the above two network models. The performance of Cascade forward back propogation network model is better than the Feed forward back propagation network model
关键词：Iris Recognition; Biometric Identification; Pattern Recognition; Automatic Segmentation