HAL will be down for maintenance from Friday, June 10 at 4pm through Monday, June 13 at 9am. More information
Skip to Main content Skip to Navigation
Journal articles

Caractérisation et classification de textures sur images naturelles

Abstract : The existing texture classification methods are generally based on a parameter extraction stage followed by a classifier stage . Using this kind of method,for an operational application requires to take into account the risk of classes mixture in the parameters space . We propose to take profit of Gagalowicz conjecture in order ta minimise this risk . The conjecture provides us with a set of parameters which totally describe the texture. We show that a connectionnist classifier is able to deal efficiently with these parameters.
Document type :
Journal articles
Complete list of metadata

Contributor : Gilles Burel Connect in order to contact the contributor
Submitted on : Monday, May 10, 2021 - 2:34:07 PM
Last modification on : Monday, November 22, 2021 - 6:42:03 PM


  • HAL Id : hal-03222749, version 1



Gilles Burel, Jean-Yves Catros, Hugues Henocq. Caractérisation et classification de textures sur images naturelles. Traitement du Signal, Lavoisier, 1992, 9 (1), pp.33-43. ⟨hal-03222749⟩



Record views