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A Hybrid Classifier for Handwritten Mathematical Expression Recognition

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.
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Contributor : Harold Mouchère <>
Submitted on : Thursday, March 25, 2010 - 10:42:01 AM
Last modification on : Tuesday, December 8, 2020 - 9:40:30 AM




Ahmad-Montaser Awal, Harold Mouchère, Christian Viard-Gaudin. A Hybrid Classifier for Handwritten Mathematical Expression Recognition. Electronic Imaging: Document Recognition and Retrieval XVI, Jan 2010, San José, United States. pp.753410-753410, ⟨10.1117/12.840023⟩. ⟨hal-00466874⟩



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