Local reasoning in fuzzy attribute graphs for optimizing sequential segmentation

Authors:
Geoffroy Fouquier;Jamal Atif;Isabelle Bloch
Affiliations:
ENST, GET-Telecom Paris, Dept. TSI, CNRS, UMR, LTCI, Paris Cedex 13, France and EPITA Research and Development Laboratory, Le Kremlin Bicêtre, France;Groupe de Recherche sur les Energies Renouvelables, Université des Antilles et de la Guyane, Cayenne;ENST, GET-Telecom Paris, Dept. TSI, CNRS, UMR, LTCI, Paris Cedex 13, France
Venue:
GbRPR'07 Proceedings of the 6th IAPR-TC-15 international conference on Graph-based representations in pattern recognition
Year:
2007

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Abstract

Spatial relations play a crucial role in model-based image recognition and interpretation due to their stability compared to many other image appearance characteristics. Graphs are well adapted to represent such information. Sequential methods for knowledge-based recognition of structures require to define in which order the structures have to be recognized. We propose to address this problem of order definition by developing algorithms that automatically deduce sequential segmentation paths from fuzzy spatial attribute graphs. As an illustration, these algorithms are applied on brain image understanding.