Improving the matching of graphs generated from shapes by the use of procrustes distances into a clique-based MAP formulation

Structural graph matching methods often fail when trying to match graphs which are small and present low structural constraints. An extra source of information is needed in order to eliminate the ambiguities produced by the lack of structural information. In this paper we introduce positional information into the cliques model in order to enhance the matching criterion. Procrustes methods provide a proper framework to do statistics with coordinate positions. Results show that our model significantly improves the matching capability in graphs generated from shapes (handwritten capital letters).