Computing Entropy Maps of Finite-Automaton-Encoded Binary Images (Extended Abstract)

) Mark G. Eramian Department of Computer Science University of Western Ontario London, Ontario, N6A 5B7, Canada [email protected] Abstract. Finite automata are being used to encode images. Applications of this technique include image compression, and extraction of self similarity information and Hausdorff dimension of the encoded image. Jurgensen and Staiger [6] proposed a method by which the local Hausdorff dimension of the encoded image could be effectively computed. This paper describes the first implementation of this procedure and presents some experimental results showing local entropy maps computed from images represented by finite automata. 1 Introduction Local entropy (Hausdorff dimension) measures of images are of interest because the local entropy of an image is closely related to local texture. If we can map texture, it is possible to map the boundaries of objects in the image, or to simply map relative differences over the image. Image texture mapping tech..