Neighborhood graphs and image processing

François Angot (1) , Régis Clouard (1) , Abderrahim Elmoataz (1) , Marinette Revenu (1)

1 Equipe Image - Laboratoire GREYC - UMR6072

Many image processing and image segmentation problems, in two or three dimensions, can be addressed and solved by methods and tools developed within the graph theory. Two types of graphs are studied: neighborhood graphs (with the duals Voronoi diagram and Delaunay graph) and adjacency graphs. In this paper, we propose an image representation based on graphs: the graph object, together with methods for attributing and weighting the graph, and methods to merge nodes, is defined within an object-oriented library of image processing operators. In order to demonstrate the interest of the approach, several applications dealing with 2D images are briefly described and discussed: we show that this change of representation can greatly simplify the tuning of image processing plans and how to replace complex sequences of image operators by one single basic operation on graphs. As results are promising, our library of graph operators is being extended to 3D images.

Domaines: Traitement des images [eess.IV]

François Angot, Régis Clouard, Abderrahim Elmoataz, Marinette Revenu. Neighborhood graphs and image processing. SPIE European Symposium on Lasers, Optics, and Vision for Productivity in Manufacturing, 1996, Besançon, France. pp.12-23. ⟨hal-00980226⟩