Spatial Morphological Covariance Applied to Texture Classification

Abstract : Morphological covariance, one of the most frequently employed texture analysis tools offered by mathematical morphology, makes use of the sum of pixel values, i.e. “volume” of its input. In this paper, we investigate the potential of alternative measures to volume, and extend the work of Wilkinson (ICPR'02) in order to obtain a new covariance operator, more sensitive to spatial details, namely the spatial covariance. The classification experiments are conducted on the publicly available Outex 14 texture database, where the proposed operator leads not only to higher classification scores than standard covariance, but also to the best results reported so far for this database when combined with an adequate illumination invariance model.
Type de document :
Communication dans un congrès
International Workshop on Multimedia Content Representation, Classification and Security (IWMRCS), 2006, Turkey. Springer, 4105, pp.522-529, 2006, Lecture Notes in Computer Science. <10.1007/11848035_69>
Liste complète des métadonnées


https://hal.archives-ouvertes.fr/hal-00516085
Contributeur : Sébastien Lefèvre <>
Soumis le : mercredi 8 septembre 2010 - 16:44:51
Dernière modification le : mercredi 8 septembre 2010 - 21:20:54
Document(s) archivé(s) le : jeudi 9 décembre 2010 - 02:50:12

Fichier

mcrcs2006.pdf
Fichiers produits par l'(les) auteur(s)

Identifiants

Collections

Citation

Erchan Aptoula, Sébastien Lefèvre. Spatial Morphological Covariance Applied to Texture Classification. International Workshop on Multimedia Content Representation, Classification and Security (IWMRCS), 2006, Turkey. Springer, 4105, pp.522-529, 2006, Lecture Notes in Computer Science. <10.1007/11848035_69>. <hal-00516085>

Partager

Métriques

Consultations de
la notice

81

Téléchargements du document

88