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Bernoulli HMMs at subword level for handwritten word recognition

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Bernoulli HMMs at subword level for handwritten word recognition

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Nombre: Giménez;Alfons Juan ...
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dc.contributor.author Giménez Pastor, Adrián es_ES
dc.contributor.author Juan, Alfons es_ES
dc.date.accessioned 2015-06-04T13:08:30Z
dc.date.available 2015-06-04T13:08:30Z
dc.date.issued 2009
dc.identifier.issn 0302-9743
dc.identifier.uri http://hdl.handle.net/10251/51259
dc.description.abstract This paper presents a handwritten word recogniser based on HMMs at subword level (characters) in which state-emission probabilities are governed by multivariate Bernoulli probability functions. This recogniser works directly with raw binary pixels of the image, instead of conventional, real-valued local features. A detailed experimentation has been carried out by varying the number of states, and comparing the results with those from a conventional system based on continuous (Gaussian) densities. From this experimentation, it becomes clear that the proposed recogniser is much better than the conventional system es_ES
dc.description.sponsorship Work supported by the EC (FEDER) and the Spanish MEC under the MIPRCV “Consolider Ingenio 2010” research programme (CSD2007-00018), the iTransDoc research project (TIN2006-15694-CO2-01), and the FPU grant AP2005-1840. es_ES
dc.language Inglés es_ES
dc.publisher Springer Verlag (Germany) es_ES
dc.relation.ispartof Pattern Recognition and Image Analysis es_ES
dc.relation.ispartofseries Lecture Notes in Computer Science;5524
dc.rights Reserva de todos los derechos es_ES
dc.subject HMM es_ES
dc.subject Subword es_ES
dc.subject Bernoulli es_ES
dc.subject Handwritten word recognition es_ES
dc.subject.classification LENGUAJES Y SISTEMAS INFORMATICOS es_ES
dc.title Bernoulli HMMs at subword level for handwritten word recognition es_ES
dc.type Capítulo de libro es_ES
dc.identifier.doi 10.1007/978-3-642-02172-5_64
dc.relation.projectID info:eu-repo/grantAgreement/MEC//CSD2007-00018/ES/Multimodal Intraction in Pattern Recognition and Computer Visionm/ es_ES
dc.relation.projectID info:eu-repo/grantAgreement/MEC//TIN2006-15694-C02-01/ES/TRANSCRIPCION Y TRADUCCION INTERACTIVA DE DOCUMENTOS DE TEXTO ANTIGUOS/ es_ES
dc.relation.projectID info:eu-repo/grantAgreement/MEC//AP2005-1840/ 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.description.bibliographicCitation Giménez Pastor, A.; Juan, A. (2009). Bernoulli HMMs at subword level for handwritten word recognition. En Pattern Recognition and Image Analysis. Springer Verlag (Germany). 497-504. https://doi.org/10.1007/978-3-642-02172-5_64 es_ES
dc.description.accrualMethod S es_ES
dc.relation.publisherversion http://link.springer.com/chapter/10.1007%2F978-3-642-02172-5_64 es_ES
dc.description.upvformatpinicio 497 es_ES
dc.description.upvformatpfin 504 es_ES
dc.type.version info:eu-repo/semantics/publishedVersion es_ES
dc.relation.senia 38254
dc.contributor.funder European Regional Development Fund es_ES
dc.contributor.funder Ministerio de Educación y Ciencia es_ES
dc.description.references Giménez-Pastor, A., Juan-Císcar, A.: Bernoulli HMMs for Off-line Handwriting Recognition. In: Proc. of the 8th Int. Workshop on Pattern Recognition in Information Systems (PRIS 2008), Barcelona, Spain, pp. 86–91 (June 2008) es_ES
dc.description.references Günter, S., Bunke, H.: HMM-based handwritten word recognition: on the optimization of the number of states, training iterations and Gaussian components. Pattern Recognition 37, 2069–2079 (2004) es_ES
dc.description.references Gadea, M.P.: Aportaciones al reconocimiento automático de texto manuscrito. PhD thesis, Dep. de Sistemes Informàtics i Computació, València, Spain. Advisors: Vidal, E., Tosselli, A.H. (October 2007) es_ES
dc.description.references Juan, A., Vidal, E.: Bernoulli mixture models for binary images. In: Proc. of the 17th Int. Conf. on Pattern Recognition (ICPR 2004), Cambridge, UK, vol. 3 (August 2004) es_ES
dc.description.references Marti, U.V., Bunke, H.: The IAM-database: an English sentence database for offline handwriting recognition.  5(1), 39–46 (2002) es_ES
dc.description.references Rabiner, L., Juang, B.-H.: Fundamentals of speech recognition. Prentice-Hall, Englewood Cliffs (1993) es_ES
dc.description.references Romero, V., Giménez, A., Juan, A.: Explicit Modelling of Invariances in Bernoulli Mixtures for Binary Images. In: Martí, J., Benedí, J.M., Mendonça, A.M., Serrat, J. (eds.) IbPRIA 2007. LNCS (LNAI), vol. 4477, pp. 539–546. Springer, Heidelberg (2007) es_ES
dc.description.references Young, S., et al.: The HTK Book. Cambridge University Engineering Department (1995) es_ES


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