期刊名称：International Journal of Signal Processing, Image Processing and Pattern Recognition
印刷版ISSN：2005-4254
出版年度：2014
卷号：7
期号：5
页码：249-258
DOI：10.14257/ijsip.2014.7.5.22
出版社：SERSC
摘要：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.
关键词：Image segmentation; Pulse coupled neural net-work; Grayscale correlation; the ; minimum of variance ratio
