Iris Recognition Based on Wavelet Transform and Neural Network

The biometric systems for user verification are becoming more popular in this age. Iris recognition system is a new technology for user verification. This paper presents an iris detection and recognition method, which adopts Canny transform to extract iris texture feature and wavelet probabilistic neural network as iris biometric classifier. The method combines wavelet neural network and probabilistic neural network for a new classifier model were able to improve the biometrics recognition accuracy as well as the global system performance. A simple and fast training algorithm, AdaBoost, is also introduced for training the wavelet probabilistic neural network. When applying the algorithm on an iris images database, the experimental results show 100% correct classifications and the method have an efficiency feasibility and performance.