An Efficient Iris Feature Encoding and Pattern Matching for Personal Identification

Recognize people identity becomes an essential problem, Iris based biometric system provides accurate personal identification. Feature encoding and pattern matching are major task in the iris recognition. In our proposed system gives how to set a model to extract the feature of different irises and match them is especially important for it determines the results of the whole system directly. Gabor wavelets are able to provide optimum conjoint representation of a signal in space and spatial frequency. A Gabor filter is constructed by modulating a sine/cosine wave with a Gaussian. Feature Encoding was implemented by convolving the normalised iris pattern with 1-D Gabor filters. For Matching hamming distance will be calculated and accurate recognition was achieved.