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In image classification, the common texture-based meth- ods are based on image gray levels. However, the use of color information improves the classification accuracy of the colored tex- tures. In this paper, we extract texture features from the natural rock images that are used in bedrock investigations. A Gaussian band- pass filtering is applied to the color channels of the images in RGB and HSI color spaces using different scales. The obtained feature vectors are low dimensional, which make the methods computation- ally effective. The results show that using combinations of different color channels, the classification accuracy can be significantly

Rock image classification using color features in Gabor space