关键词: 纹理分类, 小波包变换, 概率神经网络, 差异演化

Abstract: The Differential Evolution（DE） method is introduced in this paper to make up the shortage of basic probabilistic neural network.Consequently，a new texture image recognition method based on Differentia Evolution probabilistic neural network is proposed.At first，it extracts the energy character with the shape of tree structure wavelet packet transform and extracts the statistical mean value，average energy，standard deviation，mean residual characteristics with the statistic method，the feature vector is obtained by the above characteristics.Then the feature vector of the texture image is trained by the Differentia Evolution probabilistic neural network，thus the texture classification is identified.The experiment result indicates：compare to the BP neural network，RBF neural network and the basic probabilistic neural network，the Differentia Evolution probabilistic neural network has the higher accuracy and the faster convergence speed.

Key words: texture classification, wavelet packet transform, probabilistic neural network, Differentia Evolution（DE）