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

  • Gerard Sanromà
  • Francesc Serratosa
  • René Alquézar
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5342)


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.


graph matching hybrid genetic algorithm procrustes analysis shape analysis cliques model 


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Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Gerard Sanromà
    • 1
  • Francesc Serratosa
    • 1
  • René Alquézar
    • 2
  1. 1.Departament d’Enginyeria Informàtica i MatemàtiquesUniversitat Rovira i VirgiliSpain
  2. 2.Departament de Llenguatges i Sistemes InformàticsUniversitat Politècnica de CatalunyaSpain

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