Textile printing pattern image segmentation based on multiscale Markov random field model in wavelet domain

To improve the color separation accuracy of textile printing patterns,this paper adopted MRF algorithm and realized texture segmentation. At first a preceding process is taken in this algorithm. Then, the image is decomposed by wavelet pyramids. In the algorithm,the segmentation on each scale can make full use of the information on all scales. The relationship between each wavelet coefficient can reflect the feature of each pixel location,and the interaction of neighborhoods can reflect the regional image segmentation. Both of these two fields constrain each other by product of joint probability,and act on the segmentation process together. The image segmentation procedure is sequentially executed from the coarsest resolution scale to the finest resolution scale,and segmentation result of the coarser scale is directly projected on the nearest finer resolution scale as its initial segmentation. The segmentation result on the finest resolution is used as the final result of the algorithm.