Fuzzy Intervals for Designing Structural Signature: An Application to Graphic Symbol Recognition

  • Muhammad Muzzamil Luqman
  • Mathieu Delalandre
  • Thierry Brouard
  • Jean-Yves Ramel
  • Josep Lladós
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6020)


The motivation behind our work is to present a new methodology for symbol recognition. The proposed method employs a structural approach for representing visual associations in symbols and a statistical classifier for recognition. We vectorize a graphic symbol, encode its topological and geometrical information by an attributed relational graph and compute a signature from this structural graph. We have addressed the sensitivity of structural representations to noise, by using data adapted fuzzy intervals. The joint probability distribution of signatures is encoded by a Bayesian network, which serves as a mechanism for pruning irrelevant features and choosing a subset of interesting features from structural signatures of underlying symbol set. The Bayesian network is deployed in a supervised learning scenario for recognizing query symbols. The method has been evaluated for robustness against degradations & deformations on pre-segmented 2D linear architectural & electronic symbols from GREC databases, and for its recognition abilities on symbols with context noise i.e. cropped symbols.


symbol recognition overlapping fuzzy interval structural signature Bayesian network 


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Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Muhammad Muzzamil Luqman
    • 1
    • 2
  • Mathieu Delalandre
    • 1
  • Thierry Brouard
    • 1
  • Jean-Yves Ramel
    • 1
  • Josep Lladós
    • 2
  1. 1.Laboratoire d’InformatiqueUniversité François Rabelais de ToursFrance
  2. 2.Computer Vision CenterUniversitat Autònoma de BarcelonaSpain

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