Hierarchical image partitioning using combinatorial maps

Yll Haxhimusa (1) , Adrian Ion (1) , Walter G. Kropatsch (1) , Luc Brun (2)

1 PRIP - Pattern Recognition and Image Processing Group
2 Equipe Image - Laboratoire GREYC - UMR6072

We present a hierarchical partitioning of images using a pairwise similarity function on a combinatorial map based representation. We used the idea of minimal spanning tree to find region borders quickly in a bottom-up way, based on local differences. The result is a hierarchy of image partitions with multiple resolutions suitable for further goal driven analysis. The algorithm can handle large variation and gradient intensity in images. Dual graph representations lack an explicit encoding of the orientation of planes, existing in combinatorial maps.

Domaines: Algorithme et structure de données [cs.DS]

Yll Haxhimusa, Adrian Ion, Walter G. Kropatsch, Luc Brun. Hierarchical image partitioning using combinatorial maps. Joint Hungarian-Austrian Conference on Image Processing and Pattern Recognition, 2005, Prague, Czech Republic. pp.179-186. ⟨hal-00815662⟩