Texture Segmentation and Edge Location of Regions in Multiband Images

Many texture classification schemes require an excessively large image area for texture analysis, use a large number of features to represent each texture or are computationally very demanding. This paper presents a segmentation method considering all image bands information that can be used on natural or synthetic texture, soft or rough motifs, it permits also distinction of different textures with few changes on the same type of patterns. The approach uses a proposed coefficient, CVE; to estimate region limits that can be used for very small to very large regions and permits correct real time texture bounder classification. The space positions among the pixels on the texel are considered. The bands or color informations are combined considering they mean value and its standard deviation by the new coefficient. This scheme is computationally very efficient and it is suitable for color texture, medical analysis or satellite image recognition. It can be used of all type of texture because the rules of what will be identified are completely given by the used and adapted to each situation.