Texture Segmentation Based on Image Model and Neural Network

This paper presents a texture segmentation approach which is based on the Markov random field model (MRF) and feed forward neural network.Image texture is modeled by the second order Gauss MRF model, and the least square error estimation is employed for the solution of model parameters. To perform texture segmentation, we introduced an improved BP algorithm to get faster learning speed. Experiment shows that better segmentation results can be obtained than the traditional Euclidean distance method.