Partitioning of texture image using two-dimensional linear prediction model

This paper presents a study on texture segmentation based on a two-dimensional linear prediction method. It begins with brief summary of the principle that the division of an image which gives the minimum of the total sum of final prediction errors over the whole image corresponds to the true segmentation. Then, the practical computation procedure is given. Finally, experiments of the application of the principle are demonstrated. The results indicate that arbitrarily-shaped texture regions can be well identified.