A Rough-Fuzzy HSV Color Histogram for Image Segmentation

A color image segmentation technique which exploits a novel definition of rough fuzzy sets and the rough-fuzzy product operation is presented. The segmentation is performed by partitioning each block in multiple rough fuzzy sets that are used to build a lower and a upper histogram in the HSV color space. For each bin of the lower and upper histograms a measure, called t index, is computed to find the best segmentation of the image. Experimental results show that the proposed method retains the structure of the color images leading to an effective segmentation.

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