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International Symposium on Neural Networks

ISNN 2009: Advances in Neural Networks – ISNN 2009 pp 135–144Cite as

Fuzzy C-Means Cluster Segmentation Algorithm Based on Modified Membership

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Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 5552))

Abstract

Fuzzy c-means (FCM) algorithm is one of the most popular methods for image segmentation. However, the standard FCM algorithm is noise sensitive because of not taking into account the spatial information in the image. In this paper, we present fuzzy c-means cluster segmentation algorithm based on modified membership (MFCMp,q) that incorporates spatial information into the membership function for clustering. The spatial function is the weighted summation of the membership function in the neighborhood of each pixel under consideration. The fast MFCMp,q algorithm(FMFCMp,q) which speeds up the convergence of MFCMp,q algorithm is achieved when the MFCMp,q algorithm is initialized by the fast fuzzy c-means algorithm based on statistical histogram. The experiments on the artificial synthetic image and real-world datasets show that MFCMp,q algorithm and FMFCMp,q algorithm can segment images more effectively and provide more robust segmentation results.

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Author information

Authors and Affiliations

  1. Institute of System Engineering, Department of Control Science and Engineering, Huazhong University of Science and Technology, Wuhan, 430074, China

    Yanling Li

  2. College of Computer and Information Technology, Xinyang Normal University, Xinyang, 464000, China

    Yanling Li & Gang Li

Authors
  1. Yanling Li
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  2. Gang Li
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Editor information

Editors and Affiliations

  1. Departamento de Control Automático,, CINVESTAV-IPN,, A.P. 14-740, Av.IPN 2508,, D.F., 07360,, México, México

    Wen Yu

  2. Deptartment of Electrical and Computer Engineering,, Stevens Institute of Technology,, NJ 07030,, Hoboken,, USA

    Haibo He

  3. Dept. of Electrical and Computer Engineering,, South Dakota School of Mines & Technology,, 501 E. St. Joseph Street,, SD 57701,, Rapid City,, USA

    Nian Zhang

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© 2009 Springer-Verlag Berlin Heidelberg

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Li, Y., Li, G. (2009). Fuzzy C-Means Cluster Segmentation Algorithm Based on Modified Membership. In: Yu, W., He, H., Zhang, N. (eds) Advances in Neural Networks – ISNN 2009. ISNN 2009. Lecture Notes in Computer Science, vol 5552. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-01510-6_16

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  • DOI: https://doi.org/10.1007/978-3-642-01510-6_16

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-01509-0

  • Online ISBN: 978-3-642-01510-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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