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Iris recognition is a part of biometric identification which offers a new solution for personal identification, authentication and security by analyzing the random pattern of the iris. The iris recognition system automatically recognizes the identity of a person from a new eye image by comparing it to the human iris patterns stored in an iris template database. The iris template database is created using three steps the first step is segmentation. Hough transform is used to segment the iris region from the eye image of the CASIA database. The noise due to eyelid occlusions, reflections is eliminated in the segmentation stage. The next step is normalization. A technique based on Hough Transform was employed on the iris for creating a dimensionally consistent representation of the iris region. The last step is feature extraction. In this Local Binary Pattern and Gray level Cooccurence Matrix are used to extract the features. At last Template of the new eye image will be compared with the iris template database using Probabilistic Neural Network. Keywords—Image preprocessing, Segmentation, Normalization, Feaure Extraction, Classifier

ATM Security System using Iris Recognition by Image Processing