Application-independent feature selection for texture classification
Pattern Recognition
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This paper presents a methodology that uses formal languages representation for image processing for automatically detecting texture patterns and determining texture paths in images. The texture paths are detected and extracted by using image processing techniques, such as image segmentation to isolate regions of interest, and then the extraction of repeating textures. The detection of the texture blocks is obtained by recursively using 27 X 27, 9 X 9, and 3 X 3 windows. Predefined repeating texture patterns are also searched for in each of the sets. For each set of texture blocks with similar or same characteristics, curve fitting techniques are used for association of patterns with the texture. The selected curve is split into straight line segments, and the pattern is finally represented using the defined context-free formal language methodology. The methodology has capabilities to learn texture paths associated with certain "objects", which generate them, and use this knowledge for a variety of applications. Results are shown for various color images .