Gabor-like eigenfilters for texture segmentation

Classification, segmentation and discrimination of textures are some of the most fundamental tasks in many image understanding, pattern recognition and machine vision applications. In the past two decades or so, these topics have been actively studied by many researchers and different approaches to the problem have been proposed. These approaches normally operates on a relatively small neighbourhood and therefore are most effective in segmenting the class of so called microtextures. The paper presents the framework and a method for designing the Gabor (1946) like eigenfilter, demonstrates its effectiveness in texture segmentation and provides some experimental results.