Mean shift segmentation algorithm based on bacterial colony chemotaxis

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 procedure. Experimental results show that the proposed algorithm used for image segmentation can segment images more effectively and provide more robust segmentation results.