Unifying Variational Approach and Region Growing Segmentation

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. (pdf)

Jean-Loïc Rose(a), Thomas Grenier(b), Chantal Revol-Muller(b), Christophe Odet(b)
(a)LIRIS, CNRS UMR5205, Université Lyon 2, 69676 Bron cedex, France
(b)CREATIS, CNRS UMR5220, Inserm U630, Université de Lyon, INSA de Lyon, France