Fuzzy Visibility Graph for Structural Analysis of Online Handwritten Mathematical Expressions

Arnaud Lods 1, 2, 3 Eric Anquetil 1, 2 Sébastien Macé 4, 3
1 IntuiDoc - intuitive user interaction for document
IRISA-D6 - MEDIA ET INTERACTIONS
4 IMADOC - Interprétation et Reconnaissance d’Images et de Documents
UR1 - Université de Rennes 1, INSA Rennes - Institut National des Sciences Appliquées - Rennes, CNRS - Centre National de la Recherche Scientifique : UMR6074
Abstract : This paper presents a fuzzy visibility graph representation for handwritten mathematical expressions (HME) computed over segmented symbols using learned fuzzy landscape (FL) models. The learned FL models define the relative positioning of a pair of symbols using both their morphology, their typology and their context. A Random Forest Classifier uses this relative positioning to qualify relationships between symbols. The valued fuzzy visibility graph with the FL membership is produced from this classifier's output. This graph offers an explicit representation of the HME bi-dimensional structure which is then parsed with a set of rules to produce the recognized HME. We evaluate the performance of this system on the task of HME structure recognition using provided segmented symbols with experimental results on both CROHME 2014 and 2016 datasets. We obtain results up to par with the state-of-the-art thus proving that our fuzzy visibility graphs are a strong representation for mathematical expression parsing.
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Arnaud Lods, Eric Anquetil, Sébastien Macé. Fuzzy Visibility Graph for Structural Analysis of Online Handwritten Mathematical Expressions. 15th IAPR International Conference on Document Analysis and Recognition (ICDAR2019), Sep 2019, Sydney, Australia. ⟨hal-02281462⟩

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