A randomized heuristic for scene recognition by graph matching
Maria Claudia Boeres (boeresinf.ufes.br)
Abstract: We propose a new strategy for solving the non-bijective graph matching problem in model-based pattern recognition. The search for the best correspondence between a model and an over-segmented image is formulated as a combinatorial optimization problem, defined by the relational attributed graphs representing the model and the image where recognition has to be performed, together with the node and edge similarities between them. A randomized construction algorithm is proposed to build feasible solutions to the problem. Two neighborhood structures and a local search procedure for solution improvement are also proposed. Computational results are presented and discussed, illustrating the effectiveness of the combined approach involving randomized construction and local search.
Keywords: Scene recognition, graph matching, randomized algorithm, local search, GRASP
Category 1: Applications -- Science and Engineering (Biomedical Applications )
Category 2: Combinatorial Optimization (Meta Heuristics )
Category 3: Combinatorial Optimization (Graphs and Matroids )
Citation: Research report, Catholic University of Rio de Janeiro, Department of Computer Science, February 2004.
Entry Submitted: 04/05/2004
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