Effect of Different Neural Networks on the Accuracy in Iris Patterns Recognition

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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. In this paper, the authors 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.