Improving Online Handwritten Mathematical Expressions Recognition with Contextual Modeling

Author

Awal, Ahmad-Montaser ; Mouchère, Harold ; Viard-gaudin, Christian

Author_Institution

IRCCyN/IVC, Ecole Polytech. de I´´Univ. de Nantes, Nantes, France

fYear

2010

fDate

16-18 Nov. 2010

Firstpage

427

Lastpage

432

Abstract

We propose in this paper a new contextual modelling method for combining syntactic and structural information for the recognition of online handwritten mathematical expressions. Those models are used to find the most likely combination of segmentation/recognition hypotheses proposed by a 2D segment or. Models are based on structural information concerning the layouts of symbols. They are learned from a mathematical expressions dataset to prevent the use of heuristic rules which are fuzzy by nature. The system is tested with a large base of synthetic expressions and also with a set of real complex expressions.

Keywords

Internet; fuzzy set theory; handwritten character recognition; image segmentation; mathematics computing; 2D segmentor; contextual modelling method; fuzzy rule; online handwritten mathematical expressions recognition; segmentation-recognition hypotheses; structural information; syntactic information; Contextual modeling; Handwriting recognition; Online; Structural analysis; mathematical expressions;

fLanguage

English

Publisher

ieee

Conference_Titel

Frontiers in Handwriting Recognition (ICFHR), 2010 International Conference on

Conference_Location

Kolkata

Print_ISBN

978-1-4244-8353-2

Type

conf

DOI

10.1109/ICFHR.2010.73

Filename

5693601