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 τ 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.
A Rough-Fuzzy HSV Color Histogram for Image Segmentation
FERONE, Alessio;PETROSINO, Alfredo
2011-01-01
Abstract
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 τ 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.File in questo prodotto:
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