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Proceedings Paper

Hierarchical multiresolution texture image segmentation
Author(s): Kidiyo Kpalma; Veronique Haese-Coat; Joseph Ronsin
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Paper Abstract

In this work we present a method for multiresolution texture image segmentation via supervised Bayesian classification. This method takes into account a function called classification index CI (or Indice de Classification IC3). This function measures the accuracy rate of a pixel classification after it has been classified. The CI measure is based on the location of the pixel attribute vector in the observation space relative to the classes to which it must be classified. To reduce the time used in the classification process, we propose a new method (ASH: Algorithme de Segmentation Hierarchique3) that segments hierarchically the multiresolution images.

Paper Details

Date Published: 22 October 1993
PDF: 8 pages
Proc. SPIE 2094, Visual Communications and Image Processing '93, (22 October 1993); doi: 10.1117/12.158003
Show Author Affiliations
Kidiyo Kpalma, Institut National des Sciences Appliquees/Rennes (France)
Veronique Haese-Coat, Institut National des Sciences Appliquees/Rennes (France)
Joseph Ronsin, Institut National des Sciences Appliquees/Rennes (France)


Published in SPIE Proceedings Vol. 2094:
Visual Communications and Image Processing '93
Barry G. Haskell; Hsueh-Ming Hang, Editor(s)

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