Pretreatment Approaches for Texture Image Segmentation

Abstract

In this paper, we present two approaches of the image texture pretreatment. The reason behind it is to reduce the number of the grey level in the image, by assigning to each pixel a value that characterizes the local information of the neighborhood of this same pixel. This coding process will allow us to reduce the size of the co-occurrence matrix and also minimize the extraction time of Haralick features. We compare these pretreatment approaches by applying them on our unsupervised segmentation method of the image texture, which is based on both Kohonen maps and mathematical morphology. Our comparative study covers the results obtained by each pretreatment approach taking into consideration the execution time and the error rate.