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

Muhammad Muzzamil Luqman (1, 2) , Mathieu Delalandre (1) , Thierry Brouard (1) , Jean-Yves Ramel (1) , Josep Lladós (2)

1 LIFAT - Laboratoire d'Informatique Fondamentale et Appliquée de Tours
2 CVC - Computer Vision Center (Centre de visio per computador)

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.

Mots clés: symbol recognition; overlapping fuzzy interval; structural signature; Bayesian network

Domaines: Vision par ordinateur et reconnaissance de formes [cs.CV]

Muhammad Muzzamil Luqman, Mathieu Delalandre, Thierry Brouard, Jean-Yves Ramel, Josep Lladós. Fuzzy Intervals for Designing Structural Signature: An Application to Graphic Symbol Recognition. J.-M. Ogier,W. Liu, and J. Llad'os. Graphics Recognition. Achievements, Challenges, and Evolution, Springer Berlin / Heidelberg, pp.12-24, 2010, Lecture Notes in Computer Science, Volume 6020. ⟨hal-00502825⟩