Texture based segmentation using graph cut and Gabor filters
M. Jirik, Tomáš Ryba, Miloš Železný · Pattern Recognition and Image Analysis · 2011
This paper describes a method for texture based segmentation. Texture features are extracted by applying a bank of Gabor filters using two-sided convolution strategy. Probability texture model is represented by Gaussian mixture that is trained with the Expectation-maximization algorithm. Texture similarity, obtained this way, is used like the input of a Graph cut method. We show that the combination of texture analysis and the Graph cut method produce good results.