An Efficient authentication By Iris Using Log Gabor Filter and Neural network

Iris recognition is one of the reliable and more stable biometric recognition for authenticating person which is very interesting and active topic in research and practical application. Iris recognition system consists of localization of the iris region and generation of data set of iris images followed by iris pattern recognition. In this paper, 2D wavelet transform is applied to the raw image to reduce the size then the localization of the iris region is done by using Circular Hough transform (CHT). The Log Gabor filter is employed to extract the iris features from the normalised image. It is represented by a data set. Using this data set a Neural Network (NN) is used for the classification of iris patterns. The adaptive learning strategy is applied for training of the NN. The results of simulations illustrate the effectiveness of the neural system in personal identification.