This work concentrates on the edge detection and segmentation methods of texture images, their effectiveness with comparisons. Texture analysis, different texture models, a new and a number of existing texture segmentation methods, edge detection methods (e.g. sobel, canny, susan and statistical methods etc.), clustering techniques (hierarchical and k-means), and feed forward neural networks like self organizing maps have been systematically investigated and explored. A brief overview of these methods and implementation results are given. As a contribution a new statistical texture...