  This paper proposes a novel algorithm for the problem of structural image
segmentation through an interactive model-based approach. Interaction is
expressed in the model creation, which is done according to user traces drawn
over a given input image. Both model and input are then represented by means of
attributed relational graphs derived on the fly. Appearance features are taken
into account as object attributes and structural properties are expressed as
relational attributes. To cope with possible topological differences between
both graphs, a new structure called the deformation graph is introduced. The
segmentation process corresponds to finding a labelling of the input graph that
minimizes the deformations introduced in the model when it is updated with
input information. This approach has shown to be faster than other segmentation
methods, with competitive output quality. Therefore, the method solves the
problem of multiple label segmentation in an efficient way. Encouraging results
on both natural and target-specific color images, as well as examples showing
the reusability of the model, are presented and discussed.
