Multivalued label diffusion for semi-supervised segmentation

Pierre Buyssens (1) , Olivier Lézoray (1)

1 Equipe Image - Laboratoire GREYC - UMR6072

Diffusion methods have proven their efficiency for tasks such as semi-supervised segmentation. The introduction of patches as a part of their speed function allows to deal with textured images. However, the computational burden with such variants stays too important for low-level tasks. In this paper, we propose a multivalued color-based potential function that partly alleviates this flaw. It allows to efficiently perform semi-supervised segmentation of natural and textured images.

Mots clés: Diffusion; Gaussian Mixture Models; Semi-supervised segmentation; Textured images

Domaines: Traitement du signal et de l'image [eess.SP]; Traitement des images [eess.IV]

Pierre Buyssens, Olivier Lézoray. Multivalued label diffusion for semi-supervised segmentation. International Conference on Image Processing, Sep 2015, Québec City, Canada. ⟨hal-01153773⟩