PCNN image segmentation method based on bactrial foraging optimization algorithm

Abstract:

To handle the difficult task of setting the relative parameters properly in the research and application of Pulse Coupled Neural Networks (PCNN), an improved PCNN algorithm is proposed. It uses the maximum between-cluster variance function as the fitness function of bacterial foraging optimization algorithm, and adopts bacterial foraging optimization algorithm to search the optimal parameters, and eliminates the trouble of manually setting the experiment parameters. Experimental results show that the proposed algorithm can effectively complete document image segmentation, and result of the segmentation is obviously better than the contrast algorithms.