Rice paper classification study based on signal processing and statistical methods in image texture analysis

Texture analysis plays an important role in image processing. In the texture analysis field, the regular texture has been studied a lot, but the natural texture with complex backgrounds is less studied. In this paper we bring texture analysis into the study of rice paper´s classification. First of all we show the processing flow chart of rice paper classification. By comparing the different kinds of texture analysis methods we choose the LAWS texture method and uncertainty texture spectrum method to achieve the rice paper classification. When we use the two texture analysis methods separately, the classification accuracy of rice paper is lower. So we try to combine the two texture analysis methods. The experimental results show that the classification result when we combine the two texture analysis methods is better than the result when we only use one single texture analysis method. The classification accuracy of rice paper has been distinctly improved after the combination of the two texture analysis methods.