A hybrid classifier for handwritten mathematical expression recognition

Ahmad-Montaser Awal; Harold Mouchère; Christian Viard-Gaudin

doi:10.1117/12.840023

18 January 2010 A hybrid classifier for handwritten mathematical expression recognition

Ahmad-Montaser Awal, Harold Mouchère, Christian Viard-Gaudin

Proceedings Volume 7534, Document Recognition and Retrieval XVII; 753410 (2010) https://doi.org/10.1117/12.840023
Event: IS&T/SPIE Electronic Imaging, 2010, San Jose, California, United States

Abstract

In this paper we propose a hybrid symbol classifier within a global 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 deal with the junk problem encountered when a segmentation graph approach is used, we consider a two level classifier. A symbol classifier cooperates with a second classifier specialized to accept or reject a segmentation hypothesis. 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.

Citation Download Citation

Ahmad-Montaser Awal, Harold Mouchère, and Christian Viard-Gaudin "A hybrid classifier for handwritten mathematical expression recognition", Proc. SPIE 7534, Document Recognition and Retrieval XVII, 753410 (18 January 2010); https://doi.org/10.1117/12.840023

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