ENTROPY MEASURES IN IMAGE CLASSIFICATION

The chapter introduces new entropy measures that use the image information content such as grey levels and their topological distribution in the image domain in order to perform the classification of the image itself. The main aim of the chapter is to study the role of the image entropy in perceptual tasks and to compare the proposed approach with others well-known methods. Experiments have been carried out on medical images (mammograms) due to their variability and complexity. The image entropy approach seems to work quite well and it is less time-consuming if compared with the other methods.