Towards Handwritten Mathematical Expressions Recognition

Ahmad-Montaser A.M. Awal (1) , Harold Mouchère (1) , Christian Viard-Gaudin (1)

1 IRCCyN - Institut de Recherche en Communications et en Cybernétique de Nantes

In this paper, we propose a new framework for online handwritten mathematical expression recognition. The proposed architecture aims at handling mathematical expression recognition as a simultaneous optimization of symbol segmentation, symbol recognition, and 2D structure recognition under the restriction of a mathematical expression grammar. To achieve this goal, we consider a hypothesis generation mechanism supporting a 2D grouping of elementary strokes, a cost function defining the global likelihood of a solution, and a dynamic programming scheme giving at the end the best global solution according to a 2D grammar and a classifier. As a classifier, a neural network architecture is used; it is trained within the overall architecture allowing rejecting incorrect segmented patterns. The proposed system is trained with a set of synthetic online handwritten mathematical expressions. When tested on a set of real complex expressions, the system achieves promising results at both symbol and expression interpretation levels.

Domaines: Traitement du signal et de l'image [eess.SP]; Traitement du texte et du document; Traitement du signal et de l'image [eess.SP]

Ahmad-Montaser A.M. Awal, Harold Mouchère, Christian Viard-Gaudin. Towards Handwritten Mathematical Expressions Recognition. 10th International Conference on Document Analysis and Recognition, ICDAR 2009, Jul 2009, Barcelone, Spain. pp.1046-1050, ⟨10.1109/ICDAR.2009.71⟩. ⟨hal-00463115⟩