Automated color image edge detection using improved PCNN model

Authors:
Liang Zhou;Yu Sun;Jianguo Zheng
Affiliations:
Glorious Sun School of Business & Management, Donghua University, Shanghai, China;Glorious Sun School of Business & Management, Donghua University, Shanghai, China;Glorious Sun School of Business & Management, Donghua University, Shanghai, China
Venue:
WSEAS Transactions on Computers
Year:
2008

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Abstract

Recent researches indicate that pulse coupled neural network can be used for image processing, such as image segmentation and edge detection effectively. However, up to now it has mainly been used for the processing of gray images or binary images, and the parameters of the network are always adjusted and confirmed manually for different images, which impede PCNN's application in image processing. To solve these problems, based on the model of Pulse Coupled Neural Network and the model of HIS, this paper bring forward an improved PCNN model in the color image segmentation with the parameters determined by images' spatial and gray characteristics automatically at the first, then use the above model to obtain the edge information. The experiment results show the good effect of the new PCNN model.