A new algorithm of image segmentation based on pulse-coupled neural networks and the entropy of images
YD Ma, RL Dai, Luya Lian, Shurui Fei · Lanzhou University Institutional Repository · 2001
As all known, the performance of the image segmentation depends not only directly on the adjustment of PCNN parameters and the statistical properties of image but also on the cyclic iteration times, N, of PCNN. If the parameters have been properly set, it turns out to be essential to select a suitable criterion to determine N. While N is usually determined by means of visual judgement which decreases the efficient of PCNN image segmentation. This article raises a new method to implement the image segmentation automatically based on the PCNN model and the entropy of image. It is the criterion of maximal entropy of segmented binary image of PCNN output. According to this criterion, the iteration times, N, is determined automatically.