Combinatorial Maps for 2D and 3D Image Segmentation
Résumé
This chapter shows how combinatorial maps can be used for
2D or 3D image segmentation. We start by introducing combinatorial
maps and we show how they can be used to describe
image partitions. Then, we present a generic segmentation algorithm
that uses and modifies the image partition represented by a
combinatorial map. One advantage of this algorithm is that one can
mix different criteria and use different image features which can be
associated with the cells of the partition. In particular, it is interesting that the topological properties of the image
partition can be controlled through this approach. This property is illustrated by the computation of
classical topological invariants, known as Betti numbers, which are
then used to control the number of cavities or the number of tunnels of
regions in the image partition. Finally, we present some experimental
results of 2D and 3D image segmentation using different criteria
detailed in this chapter.
Domaines
Informatique [cs]Origine | Fichiers produits par l'(les) auteur(s) |
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