Interactive segmentation based on component-trees

Nicolas Passat (1) , Benoît Naegel (2) , François Rousseau (1) , Mériam Koob (3) , Jean-Louis Dietemann (3)

1 LSIIT - Laboratoire des Sciences de l'Image, de l'Informatique et de la Télédétection
2 LORIA - Laboratoire Lorrain de Recherche en Informatique et ses Applications
3 LINC - Laboratoire d'Imagerie et de Neurosciences Cognitives

Component-trees associate to a discrete grey-level image a descriptive data structure induced by the inclusion relation between the binary components obtained at successive level-sets. This article presents an original interactive segmen- tation methodology based on component-trees. It consists of the extraction of a subset of the image component-tree, enabling the generation of a binary object which fits at best (with respect to the grey-level structure of the image) a given binary target selected beforehand in the image. A proof of the algorithmic efficiency of this methodological scheme is proposed. Concrete application examples on magnetic resonance imaging (MRI) data emphasise its actual computational efficiency and its usefulness for interactive segmentation of real images.

Mots clés: mathematical morphology; component-tree; grey-level images; interactive segmentation

Domaines: Traitement des images [eess.IV]; Imagerie médicale

Nicolas Passat, Benoît Naegel, François Rousseau, Mériam Koob, Jean-Louis Dietemann. Interactive segmentation based on component-trees. Pattern Recognition, 2011, 44 (10-11), pp.2539-2554. ⟨10.1016/j.patcog.2011.03.025⟩. ⟨hal-00687001⟩