Hierarchical multiresolution texture image segmentation

Kidiyo Kpalma; Veronique Haese-Coat; Joseph Ronsin

doi:10.1117/12.158003

22 October 1993 Hierarchical multiresolution texture image segmentation

Kidiyo Kpalma, Veronique Haese-Coat, Joseph Ronsin

Proceedings Volume 2094, Visual Communications and Image Processing '93; (1993) https://doi.org/10.1117/12.158003
Event: Visual Communications and Image Processing '93, 1993, Cambridge, MA, United States

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.

Citation Download Citation

Kidiyo Kpalma, Veronique Haese-Coat, and Joseph Ronsin "Hierarchical multiresolution texture image segmentation", Proc. SPIE 2094, Visual Communications and Image Processing '93, (22 October 1993); https://doi.org/10.1117/12.158003

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