A string based method to recognize symbols and structural textures in architectural plans

  • Josep Lladós
  • Gemma Sánchez
  • Enric Martí
Symbol Recognition
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1389)


This paper deals with the recognition of symbols and structural textures in architectural plans using string matching techniques. A plan is represented by an attributed graph whose nodes represent characteristic points and whose edges represent segments. Symbols and textures can be seen as a set of regions, i.e. closed loops in the graph, with a particular arrangement. The search for a symbol involves a graph matching between the regions of a model graph and the regions of the graph representing the document. Discriminating a texture means a clustering of neighbouring regions of this graph. Both procedures involve a similarity measure between graph regions. A string codification is used to represent the sequence of outlining edges of a region. Thus, the similarity between two regions is defined in terms of the string edit distance between their boundary strings. The use of string matching allows the recognition method to work also under presence of distortion.


Input Graph String Match Graph Match Texture Region Edit Operation 
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 1998

Authors and Affiliations

  • Josep Lladós
    • 1
  • Gemma Sánchez
    • 1
  • Enric Martí
    • 1
  1. 1.Computer Vision Center — Dep. InformhticaUniversitat Autònoma de BarcelonaBellaterra (Barcelona)Spain

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