Hybrid Genetic Algorithm and Procrustes Analysis for Enhancing the Matching of Graphs Generated from Shapes

Authors:
Gerard Sanromà;Francesc Serratosa;René Alquézar
Affiliations:
Departament d'Enginyeria Informàtica i Matemàtiques, Universitat Rovira i Virgili, Spain;Departament d'Enginyeria Informàtica i Matemàtiques, Universitat Rovira i Virgili, Spain;Departament de Llenguatges i Sistemes Informàtics, Universitat Politècnica de Catalunya, Spain
Venue:
SSPR & SPR '08 Proceedings of the 2008 Joint IAPR International Workshop on Structural, Syntactic, and Statistical Pattern Recognition
Year:
2008

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Abstract

Typically, graphs generated via skeletonization of shape images are small and present low structural constraints. This fact constitutes a source of ambiguities for structural matching methods. Hybrid Genetic Algorithms have been effectively used for graph matching. This paper presents a new method which combines Hybrid Genetic Search with an enhanced model for graph matching. This enhanced model is based on the cliques model by Wilson and Hancock but introduces Procrustes Analysis over positional information in order to eliminate ambiguities. Comparative results are presented of the performance of the Hybrid Genetic algorithm with both the original cliques model and the enhanced model.