Image Clustering Using Graph Cuts in LAB Color Space
نویسندگان
چکیده
In this paper, we developed a novel approach that provides effective and robust segmentation of color images. It preprocesses an image by converting color information from RGB to CIE L*a*b* color spaces that CIE L*a*b* color spaces can express color in a device-independent way. CIE L*a*b* color space is better suited to digital image manipulations than the RGB space, because it had removed correlation among R, G, and B components that in RGB color space. The transfer image is then represented by using the graph structures, and the Ncut method is applied to perform globally optimized clustering and graph cut techniques was used to perform image segmentation tasks. And the experimental results show that the new algorithm performs better.
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