A Cellular Automatic Method for the Edge Detection of Images

Authors:
Yu Chen;Zhuangzhi Yan
Affiliations:
School of Communication and Information Engineering, Shanghai University, Shanghai, China 200072;School of Communication and Information Engineering, Shanghai University, Shanghai, China 200072
Venue:
ICIC '08 Proceedings of the 4th international conference on Intelligent Computing: Advanced Intelligent Computing Theories and Applications - with Aspects of Artificial Intelligence
Year:
2008

Citing 3
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Abstract

This paper present a cellular automaton (CA) based diffusion model and its application in the edge detection of images. The CA-based diffusion model consists of a regular lattice of cells with local state. These cells interact with their neighbors subject to a uniform rule which governs all cells. By setting the initial condition as an image, the diffusion model can be used as an alternative tool for diffusion equation in image processing. Experimental results showed that the CA-based diffusion model has a steady and convergent dynamical behavior and a better performance than the diffusion equation. This model can detects the image edge more accurately and suppress the noise much better than the classical edge detectors, such as LoG, Laplace, Canny and Sobel operators.