Image compression using weighted finite automata

Abstract

We introduce Weighted Finite Automata (WFA) as a tool to define real functions, in particular, greyness functions of grey-tone images. Mathematical properties and the definition power of WFA have been studied by Culik and Karhumäki. Their generative power is incomparable with Barnsley's Iterative Function Systems. Here, we given an automatic encoding algorithm that converts an arbitrary grey-tone-image (a digitized photograph) into a WFA that can regenerate it (with or without information loss). The WFA seems to be the first image definition tool with such a relatively simple encoding algorithm.