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A Cellular Automatic Method for the Edge Detection of Images

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Advanced Intelligent Computing Theories and Applications. With Aspects of Artificial Intelligence (ICIC 2008)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 5227))

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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.

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Authors and Affiliations

  1. School of Communication and Information Engineering, Shanghai University, Shanghai, 200072, China

    Yu Chen & Zhuangzhi Yan

Authors
  1. Yu Chen
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  2. Zhuangzhi Yan
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Editor information

De-Shuang Huang Donald C. Wunsch II Daniel S. Levine Kang-Hyun Jo

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© 2008 Springer-Verlag Berlin Heidelberg

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Chen, Y., Yan, Z. (2008). A Cellular Automatic Method for the Edge Detection of Images. In: Huang, DS., Wunsch, D.C., Levine, D.S., Jo, KH. (eds) Advanced Intelligent Computing Theories and Applications. With Aspects of Artificial Intelligence. ICIC 2008. Lecture Notes in Computer Science(), vol 5227. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-85984-0_112

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  • DOI: https://doi.org/10.1007/978-3-540-85984-0_112

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-85983-3

  • Online ISBN: 978-3-540-85984-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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