A fast, reliable, and objective system for computerized classification of color textured perthite images is proposed. Computerized classification of perthite textures enables large scale comparative perthite texture studies. In order to locate a perthite crystal’s borders, color and texture features are combined in a pixel classification segmentation operation, followed by probabilistic relaxation. A new operator based on vertical - horizontal run length ratios is used in order to identify and separate vein elements. Joint patch elements are disconnected using an iterative procedure that locates patch cores. After the geometrical properties are extracted, the desired distribution of the perthite texture elements is computed. Experimental classification results are presented and compared to expert manual classification.

 

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