Adaptive pyramid and semantic graph: knowledge driven segmentation

Authors:
Aline Deruyver;Yann Hodé;Eric Leammer;Jean-Michel Jolion
Affiliations:
LSIIT, UMR7005CNRS-ULP, Parc d'innovation, Illkirch CEDEX;FORENAP, CH Rouffach;Laboratoire PHASE, CNRS, Strasbourg;Laboratoire Reconnaissance de Formes et Vision, Bât. J. Verne INSA, Villeurbanne
Venue:
GbRPR'05 Proceedings of the 5th IAPR international conference on Graph-Based Representations in Pattern Recognition
Year:
2005

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Abstract

A method allowing to integrate syntactic and semantic approaches in an automatic segmentation process is described. This integration is possible thanks to the formalism of graphs. The proposed method checks the relevancy of merging criteria used in an adaptive pyramid by matching the obtained segmentation with a semantic graph describing the objects that we look for. This matching is performed by checking the arc-consistency with bilevel constraints of the chosen semantic graph. The validity of this approach is experimented on synthetic and real images.