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In this paper we present two algorithms for color image segmentation based on Huang's idea of describing the segmentation problem as the one of minimizing a suitable energy function for a Hopfield network. The first algorithm builds three different networks (one for each color feature) and then combine the results. The second builds a unique network according to the number of clusters obtained by histogram analysis. Experimental results, heuristically and quantitatively evaluated, are encouraging.

Using Hopfield networks to segment color images