An overview of fuzzy c-means based image clustering algorithms
pp. 295-310
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Abstrakt
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.
Publication details
Published in:
Abraham Ajith, Herrera Francisco, Hassanien Aboul-Ella (2009) Foundations of computational intelligence volume 2: approximate reasoning. Dordrecht, Springer.
Seiten: 295-310
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DOI: 10.1007/978-3-642-01533-5_12
Referenz:
Zhou Huiyu, Schaefer Gerald (2009) „An overview of fuzzy c-means based image clustering algorithms“, In: A. Abraham, F. Herrera & A.-E. Hassanien (eds.), Foundations of computational intelligence volume 2, Dordrecht, Springer, 295–310.