Texture Image Classification Based on Nonsubsampled Contourlet Transform and Local Binary Patterns

This paper presents a new approach of texture image classification based on nonsubsampled contourlet transform, Local binary patterns and Support vector machines. Nonsubsampled contourlet transform and Local binary patterns are used to extract texture features of images, Support vector machines are used to classify texture images. Nonsubsampled contourlet transform has translation invariability. Local Binary Patterns has rotational and gray invariance. Support vector machines have good performance in a variety of pattern recognition problems. Experimental results demonstrate that the proposed method performs much better than some existing methods. It achieves higher classification accuracy.