Contourletbased Feature Extraction for Texture Images

According to the directional property and coefficients energy feature in contourlet decomposition, we proposed a new algorithm which is adapted to extract the texture’s features. The proposed method gets the directional information by steerable filter and then gets texture features by contourlet decomposition. At last the directional feature and contourlet coefficients features are combined as texture’s feature. Because the number of contourlet decomposition level and directions can be easily modified, the number of features can be adapted to different applications. With the extracted feature vectors, we can easily distinguish different texture in standard Brodatz texture database with high classification accuracy.