Texture segmentation and matching using LBP operator and GLCM matrix

Abstract

Image processing is a dynamic research area. Recently, a lot of works have been made, efficient approaches have been developed and good results have been obtained. In this work, we propose a new texture matching and segmenting approach based on a new decomposing architecture. This method starts with one main window MW. For each iteration, the MW is reduced and all possible windows with the same size of the MW are generated. The Local Binary Pattern LBP operator, which is gray-scale invariant texture measure, and the Gray Level Co-occurrence Matrix (GLCM), which is a second order statistics measure, have been applied independently to extract the features from each generated window. Synthetic images and test images generated randomly from Brodatz album have been used in the experimentation. Good performances have been obtained and some results will be shown in the test section of this chapter. © 2014 Springer International Publishing Switzerland.