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Computer Recognition Systems pp 211–218Cite as

Image Clustering with Median and Myriad Spatial Constraint Enhanced FCM

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Part of the book series: Advances in Soft Computing ((AINSC,volume 30))

Abstract

In the current study two approaches to the clustering problem have been tested. First, a sequential analysis of -ltering and fuzzy c-means (FCM) method is performed. Then, the standard FCM has been modi-ed by adding to the objective function a second term that formulates a spatial constraint. In both approaches mean, median, and myriad are implemented. The analysis has been performed on a synthetic image and clinical images.

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References

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Author information

Authors and Affiliations

  1. Department of Biomedical Engineering, Silesian University of Technology, Gliwice, Poland

    Jacek Kawa & Ewa Pietka

Authors
  1. Jacek Kawa
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  2. Ewa Pietka
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Editor information

Editors and Affiliations

  1. Faculty of Electronics, Wroclaw University of Technology, Wybrzeze Wyspianskiego 27, 50-370, Wroclaw, Poland

    Marek Kurzyński , Edward Puchała , Michał Woźniak  & Andrzej żołnierek , ,  & 

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© 2005 Springer-Verlag Berlin Heidelberg

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Kawa, J., Pietka, E. (2005). Image Clustering with Median and Myriad Spatial Constraint Enhanced FCM. In: Kurzyński, M., Puchała, E., Woźniak, M., żołnierek, A. (eds) Computer Recognition Systems. Advances in Soft Computing, vol 30. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-32390-2_23

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  • DOI: https://doi.org/10.1007/3-540-32390-2_23

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-25054-8

  • Online ISBN: 978-3-540-32390-7

  • eBook Packages: EngineeringEngineering (R0)

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