@InProceedings{MuhammadMuzzamilLuqman2010,
author="Muhammad Muzzamil Luqman
and Thierry Brouard
and Jean-Yves Ramel
and Josep Llados",
title="Vers une approche foue of encapsulation de graphes: application a la reconnaissance de symboles",
booktitle="Colloque International Francophone sur l{\textquoteright}{\'E}crit et le Document",
year="2010",
pages="169--184",
optkeywords="Fuzzy interval",
optkeywords="Graph embedding",
optkeywords="Bayesian network",
optkeywords="Symbol recognition",
abstract="We present a new methodology for symbol recognition, by employing a structural approach for representing visual associations in symbols and a statistical classifier for recognition. A graphic symbol is vectorized, its topological and geometrical details are encoded by an attributed relational graph and a signature is computed for it. Data adapted fuzzy intervals have been introduced for addressing the sensitivity of structural representations to noise. 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, and is deployed in a supervised learning scenario for recognizing query symbols. Experimental results on pre-segmented 2D linear architectural and electronic symbols from GREC databases are presented.",
optnote="DAG",
optnote="exported from refbase (http://refbase.cvc.uab.es/show.php?record=1293), last updated on Mon, 15 May 2017 12:39:03 +0200"
}