A biometric system of identification and authentication provides automatic detection of an individual based on certain unique features or characteristics possessed by that individual. Iris detection is a biometric identification method that uses pattern detection on the images of the iris of an individual. Iris detection is considered as one of the most accurate biometric methods available owing to the unique epigenetic patterns of the iris. In this project, we have developed a system that can recognize human iris patterns and an analysis of the results is done. A hybrid mechanism has been used for implementation of the system. Iris localization is done by amalgamating the Canny Edge Detection scheme and Sobel Operator. The iris images are then normalized so as to transform the iris region to have fixed dimensions in order to allow comparisons. Feature encoding has been used to extract the most discriminating features of the iris and is done using a modification of Gabor wavelets. And finally the biometric templates are compared using Hamming Distance which tells us whether the two iris images are same or not.