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This paper proposes a segmentation method based on information theory. The entropy of the image is regarded as the objective function to be optimized. It is maximized during the segmenting process. At first, the kernel self-organizing map is applied to cluster the input vectors of the image into groups according to their attributes, and it keeps entropy maximization meanwhile. Then the clustering...
Mean shift, like other gradient ascent optimization methods, is susceptible to local maxima, and hence often fails to find the desired global maximum. For this reason, mean shift segmentation algorithm based on bacterial colony chemotaxis (BCC) is proposed in this paper. The mean shift vector is firstly optimized using BCC algorithm. Then, the optimal mean shift vector is updated using mean shift...
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