Reconnaissance et détection robuste d'objets couleur

Dans cet article, nous présentons une nouvelle approche de reconnaissance, d'objets basée sur l'utilisation des moments Zernike appliqués sur des images couleur. La détection d'objets repose sur une approche utilisant une segmentation couleur et l'étiquetage des composantes connexes. Une méthode basée sur les séparateurs à vaste marge est utilisée pour l'étape d'apprentissage et de reconnaissance. Nous illustrons la méthode proposée sur des images couleur incluant quelques objets de la base de données COIL-100

Grating cell operator features for oriented texture segmentation

The performance of two well-known texture operators (based on Gabor-energy and the cooccurrence matrix) is compared with the performance of a new, biologically motivated texture operator the grating cell operator; which was proposed elsewhere by the authors. The comparison is made using a new quantitative method, based on the Fisher criterion. Together with some classification results comparison experiments the comparison shows a clear superiority of the new operator in oriented texture problems

Grating cell operator features for oriented texture segmentation

The performance of two well-known texture operators (based on Gabor-energy and the cooccurrence matrix) is compared with the performance of a new, biologically motivated texture operator, the grating cell operator, which was proposed elsewhere by the authors. The comparison is made using a new quantitative method, based on the Fisher criterion. Together with some classification results comparison experiments the comparison shows a clear superiority of the new operator in oriented texture problems.