Texture Discrimination Using Self‐Organized Multiresolution Filtering
Hiroshi Sakou, Hitoshi Matsushima, Masakazu Ejiri · Systems and Computers in Japan · 1991
Abstract In texture discrimination the basic image processes are considered to choose effective resolution, to determine representative features and to unify subregions having the same representative features. To realize these processes, this paper presents an improved method for discriminating higher‐order features by using a self‐organized multiresolutional filter. First, we make a local transformation function with the maximum discrimination ability by a limited‐size neighborhood operation. Next, extending the method to the multiresolutional case, we let neighbor pixels of resolution which is optimal for discrimination be chosen automatically. Moreover, we realize unification of texture regions by connecting features represented by these pixel values and by obtaining macro‐features. In this paper we also describe examples in which this method is applied to extract title characters from printed pages and to extract a specific part from a map image, and show that this method using higher‐order features possess sufficient discrimination ability for real texture images.