Classifying Method of Iris Image Based on Wavelet Packet and Neural Network

By combining wavelet packet with neural network in human iris recognition, an neural network ensemble was constructed to iris classification. Iris image texture features are acquired by using wavelet packet decomposition,then through the new constructive RBF neuron networks, the training for texture classification problem of neural networks is transformed into the"including"problem of a points. A combination method of wavelet packet and neural network in pattern recognition is given.The method of pattern recognition based on combining multiple classifiers not only can reduce the long training time and learning complexity of traditional neural networks,but also can improve veracity and robustness ability in pattern recognition At the same time, the problem of harding to determine the number of hidden note is resolved in neural network,and the optimization of the neural network is also considered.