Automatic Image Segmentation with PCNN Algorithm Based on Grayscale Correlation

Abstract

In order to use pulse coupled neural networks (PCNN) for precise automatic image segmentation, we propose an improved PCNN model. We first establish a connection weight matrix based on the image local gray correlation and on the Euclid distance. We then used the minimum variance ratio criterion to automatically determine PCNN cycle times, and achieve automatic image segmentation. The simulation results show that this method can automatically determine the number of iterations PCNN, and that it is highly feasible and better segmentation effect.