Texture Detection by Genetic Programming

This paper presents an approach to blind texture detection in images based on adaptation of the 2DLookup algorithm by Genetic Programming. The task of blind texture detection is to separate textured regions of an image from non-textured (as e.g. homogeneous) ones, without any reference to a priori knowledge about image content. The 2D-Lookup algorithm, which generalizes the well-known co-occurrence matrix approach of texture analysis, is based on two arbitrary image processing operations. By Genetic Programming, those image operations can be designed and adapted to a given recognition goal of the whole algorithm. The idea to employ such a framework for texture detection is to use a random image as adaptation goal. Despite of the fact that such a task has no exact solution, the system is able to fulfill this task to a certain degree. This degree is related to textureness in the image: the more texture, the higher the degree. The paper exemplifies this approach.