Statistical Classification of Spatial Relationships among Mathematical Symbols

Authors:
Walaa Aly;Seiichi Uchida;Akio Fujiyoshi;Masakazu Suzuki
Affiliations:
-;-;-;-
Venue:
ICDAR '09 Proceedings of the 2009 10th International Conference on Document Analysis and Recognition
Year:
2009

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Recognition of on-line handwritten mathematical expressions using 2D stochastic context-free grammars and hidden Markov models

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A global learning approach for an online handwritten mathematical expression recognition system

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Abstract

In this paper, a statistical decision method for automatic classification of spatial relationships between each adjacent pair is proposed. Each pair is composed of mathematical symbols and/or alphabetical characters. Special treatment of mathematical symbols with variable size is important.This classification is important to recognize an accurate structure analysis module of math OCR. Experimental results on a very large database showed that the proposed method worked well with an accuracy of 99.57% by two important geometric feature relative size and relative position.