A fuzzy logic approach to image segmentation

A novel image segmentation algorithm derived in a fuzzy entropy framework is presented. First, the fuzzy entropy function is computed based on fuzzy region width and the Shannon´s function of the image. Then all of the local entropy maxima are located in order to find the optimal partition for image segmentation scene local entropy maxima corresponding to the uncertainties among various regions in the image. This algorithm is very effective for the images whose histograms have no clear peaks and valleys, or the number of the segmentation classes is unknown, or the probabilistic model of the image and the different segmentation classes are unknown. A large number of experiments have been carried out on different kinds of images. Good performances of the proposed algorithm have been achieved