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Spectral representations of linear features for generalisation

  • Emmanuel Fritsch
  • Jean Philippe Lagrange
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 988)

Abstract

In this paper we propose the use of new representations of linear features in order to make up for the weakness of classical generalisation algorithms. Such representations are developed from spectral tools: Fourier series and wavelet decomposition. The theoretical possibilities of representations are discussed from a generalisation point of view. Algorithms are built on these representations. The experiments are presented and discussed, particularly the encouraging results leading to caricature.

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Copyright information

© Springer-Verlag Berlin Heidelberg 1995

Authors and Affiliations

  • Emmanuel Fritsch
    • 1
  • Jean Philippe Lagrange
    • 1
  1. 1.Laboratoire CogitInstitut de Géographie NationaleSt. MandéFrance

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