Multifractals, Texture, and Image Analysis

Abstract : Image analysis using texture and multifractal paradigms is addressed. Multifractal theory and its application to image description are discussed, and it is shown that this approach allows the discrete signal to be worked on directly. A system for texture classification that is based on a learning scheme and does not make use of any a priori model is introduced. Image segmentation is then considered, and the notion of mixed classes, which allows accurate detection of texture boundaries on complex images, is introduced.
Type de document :
Communication dans un congrès
CVPR'92 - IEEE Computer Society Conference on Computer Vision and Pattern Recognition, Jun 1992, Champaign, IL, United States. IEEE, 1992, 〈10.1109/CVPR.1992.223207〉
Liste complète des métadonnées

https://hal.inria.fr/inria-00613979
Contributeur : Lisandro Fermin <>
Soumis le : lundi 8 août 2011 - 13:30:36
Dernière modification le : vendredi 25 mai 2018 - 12:02:06

Identifiants

Collections

Citation

Jacques Lévy-Vehel, Pascal Mignot, Jean-Paul Berroir. Multifractals, Texture, and Image Analysis. CVPR'92 - IEEE Computer Society Conference on Computer Vision and Pattern Recognition, Jun 1992, Champaign, IL, United States. IEEE, 1992, 〈10.1109/CVPR.1992.223207〉. 〈inria-00613979〉

Partager

Métriques

Consultations de la notice

89