A Method of Image Texture Texton Classification with Markov Random Field

In this article a new method based on MRF to classify image texture texton has been put forward. The constraint relationship between the center pixel feature value and the neighbor pixels feature value in MRF can reflect the features of image texture texton as well as different MRF parameters. Standard deviation based on the MRF parameter of the same category is the smallest. So we can use this property to classify image texture. By comparing the different experimental scheme and different classification method, we can come to the conclusion that the method of image texture element classification proposed in this paper has certain advantages, and it is a good methold of image classification.