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A New Effective and Powerful Image Segmentation Method

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Advances in Neural Networks – ISNN 2005 (ISNN 2005)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 3497))

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Abstract

A new algorithm for image segmentation named radar algorithm is proposed in this paper. The proposed algorithm is based on SOM network model, the mathematical morphology and physical simulation. This new algorithm is simple and easy to use while with powerful functions. The time complexity of the radar algorithm is 90*O(n3). Further, the proposed algorithm has better robustness. The experimental results show that the Radar algorithm is an effective and powerful image segmentation method. It has wide applications in image segmentation especially in the processing of images with discontinuous edges.

Supported by the National Natural Science Foundation of China under Grant NO.60271022 and NO.60271025.

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Author information

Authors and Affiliations

  1. School of Life Science and Technology, Xi’an Jiaotong University, Xi’an, Shaanxi, 710049, China

    Yalin Miao, Zhengzhong Bian & Gang Yu

  2. School of Electronic and Information Engineering, Xi’an Jiaotong University, Xi’an, Shaanxi, 710049, China

    Xianglin Miao & Kai Chen

Authors
  1. Yalin Miao
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  2. Xianglin Miao
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  3. Zhengzhong Bian
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  4. Kai Chen
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  5. Gang Yu
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Editor information

Editors and Affiliations

  1. Department of Mechanical and Automation Engineering, The Chinese University of Hong Kong, Shatin, New Territories, Hong Kong, China

    Jun Wang

  2. The Key Laboratory of Optoelectric Technology & Systems, Ministry of Education, China

    Xiao-Feng Liao

  3. Computational Intelligence Laboratory, School of Computer Science and Engineering, University of Electronic Science and Technology of China, 610054, Chengdu, P.R. China

    Zhang Yi

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© 2005 Springer-Verlag Berlin Heidelberg

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Miao, Y., Miao, X., Bian, Z., Chen, K., Yu, G. (2005). A New Effective and Powerful Image Segmentation Method. In: Wang, J., Liao, XF., Yi, Z. (eds) Advances in Neural Networks – ISNN 2005. ISNN 2005. Lecture Notes in Computer Science, vol 3497. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11427445_112

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  • DOI: https://doi.org/10.1007/11427445_112

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-25913-8

  • Online ISBN: 978-3-540-32067-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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