Image Segmentation with PCNN Model and Adaptive Immune Algorithm
In the field of image processing,pulse coupled neural network(PCNN) has to adjust the parameters repeatedly to obtain the good performace.For this reason,we present a novel algorithm to automatically determine PCNN parameters by combining with immune algorithm.Aimming at determining PCNN parameter automatically,the proposed method transforms PCNN parameter setting problem into the parameter optimization problem of immune algorithm and takes image entropy as the evaluation basis of the fitness.Meanwhile,in the immune algorithm,the adaptive operator and gradient operation are adopted to affect the evolution of some antibodies,so that it can keep the activity of the group and prevent falling into local optimum.Experiments show that the proposed method achieves the adaptive parameter adjustment of PCNN and yields the better segmentation performance than other methods.