Seventh International Conference on Document Analysis and Recognition (ICDAR'03) - Volume 1
On Machine Understanding of Online Handwritten Mathematical Expressions
Edinburgh, Scotland
August 03-August 06
ISBN: 0-7695-1960-1
This paper aims at automatic recognition of online handwritten mathematical expressions written on an electronic tablet. The proposed technique involves two major stages: symbol recognition and structural analysis. A multiple-classifier consists of both parametric and non-parametric classifier has been used for recognition of symbols. Parametric classifier is based on Hidden Markov Model (HMM), whereas, non-parametric classifier uses Nearest Neighbor classification scheme. Structural analysis uses several online and offline features to identify the spatial relationships among symbols. A context free grammar has been designed to convert input expressions into their corresponding Latex strings. Contextual information has been used to correct several errors occurring at both recognition and structural analysis stage. A new method for evaluating performance of the proposed systems has been formulated. Experiments on a dataset of considerable size show high efficiency of the proposed system.
Citation:
Utpal Garain, B. B. Chaudhuri, "On Machine Understanding of Online Handwritten Mathematical Expressions," icdar, vol. 1, pp.349, Seventh International Conference on Document Analysis and Recognition (ICDAR'03) - Volume 1, 2003