Fuzzy Intervals for Designing Structural Signature: An Application to Graphic Symbol Recognition
Muhammad Muzzamil Luqman, Mathieu Delal, Thierry Brouard, Jean-Yves Ramel, Josep Lladós · 2010
Abstract. The motivation behind our work is to present a new methodology for symbol recognition. The proposed method employs a structural approach for rep-resenting visual associations in symbols and a statistical classifier for recognition. We vectorize a graphic symbol, encode its topological and geometrical informa-tion 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 signa-tures 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 su-pervised 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. Key words: symbol recognition, overlapping fuzzy interval, structural signature, Bayesian network. 1