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In this paper, a Canny operator-based method using PCNN (Pulse-Coupled Neural Network) is proposed for color image segmentation. The coarse location information of the salient object and the background is first estimated based on the distribution of the detected key-points. An image is then over-segmented into super-pixels and their histograms are computed. The saliency of a super-pixel is obtained according to the maximum of variance ration and Shannon entropy. Color image segmentation is implemented using PCNN based on Canny operator edge detection method. The proposed method is compared with state-of-the-art methods on the widely used dataset, and the experiments show that it overall obtains more accurate results. [ABSTRACT FROM AUTHOR]