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Application of Fuzzy Mathematical Morphology for Unsupervised Color Pixels Classification

  • A. Gillet
  • C. Botte-Lecocq
  • L. Macaire
  • J.-G. Postaire
Conference paper
Part of the Studies in Classification, Data Analysis, and Knowledge Organization book series (STUDIES CLASS)

Abstract

In this paper, we present a new color image segmentation algorithm which is based on fuzzy mathematical morphology. After a color pixel projection into an attribute space, segmentation consists of detecting the different modes associated with homogeneous regions. In order to detect these modes, we show how a color image can be viewed as a fuzzy set with its associated membership function corresponding to a mode which is defined by a color cooccurrence matrix and by mode concavity properties. A new developed fuzzy morphological transformation is then applied to this membership function in order to identify the modes. The performance of our proposed fuzzy morphological approach is then presented using a test color image, and is then compared to the competitive learning algorithm.

Keywords

Membership Function Color Image Attribute Space Color Feature Competitive Learning 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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References

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Copyright information

© Springer-Verlag Berlin · Heidelberg 2000

Authors and Affiliations

  • A. Gillet
    • 1
  • C. Botte-Lecocq
    • 1
  • L. Macaire
    • 1
  • J.-G. Postaire
    • 1
  1. 1.Laboratoire d’Automatique I3DUniversité des Sciences et Technologies de Lille - Cité ScientifiqueVilleneuve d’AscqFrance

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