Image segmentation method based on PCNN

Aiming at determining the optimal result of Pulse-Coupled Neural Network for image segmentation, a novel method is proposed which combines the PCNN with between-cluster variance. The fired nerves and the unfired nerves of PCNN corresponding to pixels of image are considered as target and the background respectively. The between-cluster variance between the target and the background is calculated at each process of iteration. The optimal segmentation result is obtained when the maximum value of the between-cluster variance is achieved. Experimental results show that the method can achieve better image segmentation and has a common applicability. The simulation time for segmenting an image with the size of 256 by 256 is about 0.8 second.