Structural Graph Extraction from Images

  • Antonio-Javier Gallego-Sánchez
  • Jorge Calera-Rubio
  • Damián López
Part of the Advances in Intelligent and Soft Computing book series (AINSC, volume 151)


We present three new algorithms to model images with graph primitives. Our main goal is to propose algorithms that could lead to a broader use of graphs, especially in pattern recognition tasks. The first method considers the q-tree representation and the neighbourhood of regions. We also propose a method which, given any region of a q-tree, finds its neighbour regions. The second algorithm reduces the image to a structural grid. This grid is postprocessed in order to obtain a directed acyclic graph. The last method takes into account the skeleton of an image to build the graph. It is a natural generalization of similar works on trees [8, 12]. Experiments show encouraging results and prove the usefulness of the proposed models in more advanced tasks, such as syntactic pattern recognition tasks.


Directed Acyclic Graph Grid Graph Tree Automaton Location Array Pattern Recognition Task 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Antonio-Javier Gallego-Sánchez
    • 1
  • Jorge Calera-Rubio
    • 1
  • Damián López
    • 2
  1. 1.Departamento de Lenguajes y Sistemas InformáticosUniversity of AlicanteAlicanteSpain
  2. 2.Departamento de Sistemas Informáticos y ComputaciónTechnical University of ValenciaValenciaSpain

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