Texture Segmentation Program

This example focuses on texture generation and segmentation for image analysis. The implementation involves applying three distinct filtering functions to extract texture information from different image regions: entropyfilt calculates local entropy to measure texture randomness, stdfilt computes local standard deviation to assess texture variation, and rangefilt determines local range to capture texture contrast. These filtering operations help isolate and characterize texture patterns within the image for further processing. Through these filtering techniques, we obtain detailed texture feature information that enables better understanding of different image components. Therefore, this example utilizes these filtering functions to enhance texture characteristics and investigates their practical impacts and applications in image segmentation tasks. The code implementation typically involves sequential application of these filters followed by thresholding or clustering algorithms to achieve final segmentation results.