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An Overview of Fuzzy C-Means Based Image Clustering Algorithms

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Foundations of Computational Intelligence Volume 2

Part of the book series: Studies in Computational Intelligence ((SCI,volume 202))

Summary

Clustering is an important step in many imaging applications with a variety of image clustering techniques having been introduced in the literature. In this chapter we provide an overview of several fuzzy c-means based image clustering concepts and their applications. In particular, we summarise the conventional fuzzy c-means (FCM) approaches as well as a number of its derivatives that aim at either speeding up the clustering process or at providing improved or more robust clustering performance.

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Author information

Authors and Affiliations

  1. School of Engineering and Design, Brunel University, Uxbridge, U.K

    Huiyu Zhou

  2. Department of Computer Science, Loughborough University, Loughborough, U.K

    Gerald Schaefer

Authors
  1. Huiyu Zhou
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  2. Gerald Schaefer
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Editor information

Editors and Affiliations

  1. Faculty of Computers and Information Information Technology Department, Cairo University, 5 Ahmed Zewal St., Orman, Giza

    Aboul-Ella Hassanien

  2. Machine Intelligence Research Labs (MIR Labs), Scientific Network for Innovation and Research Excellence, P.O. Box 2259, 98071-2259, Auburn,Washington, USA

    Ajith Abraham

  3. Soft Computing and Intelligent Information Systems Department of Computer Science and Artificial Intelligence ETS de Ingenierias Informática y de Telecomunicación, University of Granada, E-18071, Granada, Spain

    Francisco Herrera

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Zhou, H., Schaefer, G. (2009). An Overview of Fuzzy C-Means Based Image Clustering Algorithms. In: Hassanien, AE., Abraham, A., Herrera, F. (eds) Foundations of Computational Intelligence Volume 2. Studies in Computational Intelligence, vol 202. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-01533-5_12

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  • DOI: https://doi.org/10.1007/978-3-642-01533-5_12

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-01532-8

  • Online ISBN: 978-3-642-01533-5

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