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An integrated grammar-based approach for mathematical expression recognition

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An integrated grammar-based approach for mathematical expression recognition

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dc.contributor.author Álvaro Muñoz, Francisco es_ES
dc.contributor.author Sánchez Peiró, Joan Andreu es_ES
dc.contributor.author Benedí Ruiz, José Miguel es_ES
dc.date.accessioned 2017-06-09T11:14:54Z
dc.date.available 2017-06-09T11:14:54Z
dc.date.issued 2016
dc.identifier.issn 0031-3203
dc.identifier.uri http://hdl.handle.net/10251/82650
dc.description This is the author’s version of a work that was accepted for publication in Pattern Recognition. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Pattern Recognition 51 (2016) 135–147. DOI 10.1016/j.patcog.2015.09.013. es_ES
dc.description.abstract Automatic recognition of mathematical expressions is a challenging pattern recognition problem since there are many ambiguities at different levels. On the one hand, the recognition of the symbols of the mathematical expression. On the other hand, the detection of the two-dimensional structure that relates the symbols and represents the math expression. These problems are closely related since symbol recognition is influenced by the structure of the expression, while the structure strongly depends on the symbols that are recognized. For these reasons, we present an integrated approach that combines several stochastic sources of information and is able to globally determine the most likely expression. This way, symbol segmentation, symbol recognition and structural analysis are simultaneously optimized. In this paper we define the statistical framework of a model based on two-dimensional grammars and its associated parsing algorithm. Since the search space is too large, restrictions are introduced for making the search feasible. We have developed a system that implements this approach and we report results on the large public dataset of the CROHME international competition. This approach significantly outperforms other proposals and was awarded best system using only the training dataset of the competition. (C) 2015 Elsevier Ltd. All rights reserved. es_ES
dc.description.sponsorship This work was partially supported by the Spanish MINECO under the STraDA research project (TIN2012-37475-C02-01) and the FPU Grant (AP2009-4363). en_EN
dc.language Inglés es_ES
dc.publisher Elsevier es_ES
dc.relation.ispartof Pattern Recognition es_ES
dc.rights Reserva de todos los derechos es_ES
dc.subject Mathematical expression recognition es_ES
dc.subject Probabilistic parsing es_ES
dc.subject Handwriting recognition es_ES
dc.subject.classification LENGUAJES Y SISTEMAS INFORMATICOS es_ES
dc.title An integrated grammar-based approach for mathematical expression recognition es_ES
dc.type Artículo es_ES
dc.identifier.doi 10.1016/j.patcog.2015.09.013
dc.relation.projectID info:eu-repo/grantAgreement/MINECO//TIN2012-37475-C02-01/ES/SEARCH IN TRANSCRIBED MANUSCRIPTS AND DOCUMENT AUGMENTATION/ es_ES
dc.relation.projectID info:eu-repo/grantAgreement/ME//AP2009-4363/ES/AP2009-4363/ es_ES
dc.rights.accessRights Abierto es_ES
dc.contributor.affiliation Universitat Politècnica de València. Departamento de Sistemas Informáticos y Computación - Departament de Sistemes Informàtics i Computació es_ES
dc.contributor.affiliation Universitat Politècnica de València. Escola Tècnica Superior d'Enginyeria Informàtica es_ES
dc.description.bibliographicCitation Álvaro Muñoz, F.; Sánchez Peiró, JA.; Benedí Ruiz, JM. (2016). An integrated grammar-based approach for mathematical expression recognition. Pattern Recognition. 51:135-147. https://doi.org/10.1016/j.patcog.2015.09.013 es_ES
dc.description.accrualMethod S es_ES
dc.relation.publisherversion http://dx.doi.org/10.1016/j.patcog.2015.09.013 es_ES
dc.description.upvformatpinicio 135 es_ES
dc.description.upvformatpfin 147 es_ES
dc.type.version info:eu-repo/semantics/publishedVersion es_ES
dc.description.volume 51 es_ES
dc.relation.senia 308295 es_ES
dc.contributor.funder Ministerio de Economía y Competitividad es_ES
dc.contributor.funder Ministerio de Educación es_ES


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