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Application of fuzzy mathematical morphology for pattern classification

  • Sandrine Turpin-Dhilly
  • Claudine Botte-Lecocq
Part of the Studies in Classification, Data Analysis, and Knowledge Organization book series (STUDIES CLASS)

Abstract

In this paper, we present a new approach to unsupervised pattern classification, based on fuzzy morphology. The different modes associated to each cluster are detected by means of a fuzzy morphological transformation applied to a membership function defined from the mode concavity properties. The results of this clustering method are shown using artificially generated data sets.

Key Words

Fuzzy Morphology Fuzzy structuring function Mode detection Pattern recognition Probability density function 

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Copyright information

© Springer-Verlag Berlin · Heidelberg 1998

Authors and Affiliations

  • Sandrine Turpin-Dhilly
    • 1
  • Claudine Botte-Lecocq
    • 1
  1. 1.Laboratoire d’ Automatique I3DVilleneuve d’ AscqFrance

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