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Fuzzy clustering and images reduction

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Computational Intelligence Theory and Applications (Fuzzy Days 1997)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 1226))

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Abstract

In this paper we present an efficient method for estimating the significant points of a gray level image by means of a fuzzy clustering algorithm. This method can be used to reduce the resolution of the image so it can be transmited and later reconstructed with the greatest reliability. We will show how using less than 0,01 of the original information it is possible to reconstruct an image with a considerable level of detail.

This work has been partially supported by CICYT project TIC95-1019

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References

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Author information

Authors and Affiliations

  1. Dept. Informática y Sistemas, Universidad de Murcia, Spain

    A. F. Gómez-Skarmeta & J. Piernas

  2. Dept. Ciencias de la Computación e I.A, Universidad de Granada, Spain

    M. Delgado

Authors
  1. A. F. Gómez-Skarmeta
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  2. J. Piernas
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  3. M. Delgado
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Editor information

Bernd Reusch

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© 1997 Springer-Verlag Berlin Heidelberg

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Gómez-Skarmeta, A.F., Piernas, J., Delgado, M. (1997). Fuzzy clustering and images reduction. In: Reusch, B. (eds) Computational Intelligence Theory and Applications. Fuzzy Days 1997. Lecture Notes in Computer Science, vol 1226. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-62868-1_116

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  • DOI: https://doi.org/10.1007/3-540-62868-1_116

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-62868-2

  • Online ISBN: 978-3-540-69031-3

  • eBook Packages: Springer Book Archive

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