Unifying variational approach and region growing segmentation

J.L. Rose , T Grenier , C. Revol-Muller (1) , C. Odet (1)

1 Images et Modèles

Region growing is one of the most popular image segmentation
methods. The algorithm for region growing is easily
understandable but criticized for its lack of theoretical background.
In order to overcome this weakness, we propose to
describe region growing in a new framework using a variational
approach that we called Variational Region Growing
(VRG). Variational approach is commonly used in image
segmentation methods such as active contours or level
sets, but is rather original in the context of region growing. It
relies on an evolution equation derived from an energy minimization,
that drives the evolving region towards the targeted
solution. Here, the energy minimization and the VRG robustness
to the initial seeds location are performed on gray-level
and color images.

Mots clés: region-based energy; Segmentation; variational approach; categₛt2i; Images et Modèles; methods; region growing

Domaines: Imagerie médicale

J.L. Rose, T Grenier, C. Revol-Muller, C. Odet. Unifying variational approach and region growing segmentation. 18th European Signal Processing Confernce (EUSIPCO-2010), 2010, Aalborg, Denmark. pp.1781-1785. ⟨hal-01871245⟩