Abstract: This paper proposed a feature extraction method based on the contourlet transform and Invariant moments.First it should be transformed using contourlet transform for analysis with multi scale and multi directional,and then extract the statistical characteristics and moment invariant features of the subband coefficient, constructed as feature vector.The feature vector is weighted according to the degrees of classificion,and the feature with higher classification ability has bigger weight,which are calculated to get some new feature vectors.At last, classify the extracted feature vectors by RBF Neural network which works as a classifier.The experimental results proved the effectiveness of the methods and the better classification ability.