Structure tensor based analysis of touching grain kernels for visual grading - Archive ouverte HAL Accéder directement au contenu
Pré-Publication, Document De Travail Année : 2015

Structure tensor based analysis of touching grain kernels for visual grading

Résumé

Automatic visual grading of seed lots with a high density of touching grain kernels is a challenging problem. The structure tensor is a simple and robust descriptor that was developed to analyze textures orientation. Contrarily to segmentation methods which rely on an object based modelling of images, the structure tensor views the sample at a macroscopic scale, like a continuum. Thanks to this tool, it is possible to extract useful information on the orientation of grain kernels even in a bulk. Knowing the rough orientation of a grain kernel could provide an initialization for segmentation techniques. The comparative results with ground truth orientations on four different grain kernels demonstrate the ability of the structure tensor to detect the seed orientations.
Fichier principal
Vignette du fichier
2015_Structure_tensor_based_analysis_of_touching_grain_kernels_for_visual_grading.pdf (4.38 Mo) Télécharger le fichier
Origine : Fichiers produits par l'(les) auteur(s)
Loading...

Dates et versions

hal-01112445 , version 1 (02-02-2015)

Identifiants

  • HAL Id : hal-01112445 , version 1

Citer

Stanislas Larnier. Structure tensor based analysis of touching grain kernels for visual grading. 2015. ⟨hal-01112445⟩
175 Consultations
163 Téléchargements

Partager

Gmail Facebook X LinkedIn More