Towards a Handwritten Text Interpretation Framework for Ancient Spanish Manuscripts

Autores
Xamena, Eduardo; Orozco, Carlos Ismael; Carrasco Cabrera, Gastón
Año de publicación
2019
Idioma
inglés
Tipo de recurso
documento de conferencia
Estado
versión publicada
Descripción
Handwritten Text Recognition is an extensively studied research topic.We implement a widely known binarization method in order to preprocess handwritten text images efficiently and accurately, acquiring adequate binary black-white images for later recognition processes. Afterwards, the characters present in the documents are used to train and evaluate deep-learning mechanisms for the recognition task. Our framework provides good source images for the recognition phase in terms of noise removal and processing of low contrast images. Besides, the process of character recognition is also improved by means of deep-learning techniques.
Sociedad Argentina de Informática e Investigación Operativa
Materia
Ciencias Informáticas
Handwritten text recognition
Convolutional Neural Networks
Binarization
Document images
Nivel de accesibilidad
acceso abierto
Condiciones de uso
http://creativecommons.org/licenses/by-nc-sa/3.0/
Repositorio
SEDICI (UNLP)
Institución
Universidad Nacional de La Plata
OAI Identificador
oai:sedici.unlp.edu.ar:10915/89180
Acceder
id SEDICI_ecedff1f295525e475d90ba3176cb553
oai_identifier_str oai:sedici.unlp.edu.ar:10915/89180
network_acronym_str SEDICI
repository_id_str 1329
network_name_str SEDICI (UNLP)
spelling Towards a Handwritten Text Interpretation Framework for Ancient Spanish ManuscriptsXamena, EduardoOrozco, Carlos IsmaelCarrasco Cabrera, GastónCiencias InformáticasHandwritten text recognitionConvolutional Neural NetworksBinarizationDocument imagesHandwritten Text Recognition is an extensively studied research topic.We implement a widely known binarization method in order to preprocess handwritten text images efficiently and accurately, acquiring adequate binary black-white images for later recognition processes. Afterwards, the characters present in the documents are used to train and evaluate deep-learning mechanisms for the recognition task. Our framework provides good source images for the recognition phase in terms of noise removal and processing of low contrast images. Besides, the process of character recognition is also improved by means of deep-learning techniques.Sociedad Argentina de Informática e Investigación Operativa2019-09info:eu-repo/semantics/conferenceObjectinfo:eu-repo/semantics/publishedVersionObjeto de conferenciahttp://purl.org/coar/resource_type/c_5794info:ar-repo/semantics/documentoDeConferenciaapplication/pdf28-34http://sedici.unlp.edu.ar/handle/10915/89180enginfo:eu-repo/semantics/altIdentifier/issn/2683-8990info:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by-nc-sa/3.0/Creative Commons Attribution-NonCommercial-ShareAlike 3.0 Unported (CC BY-NC-SA 3.0)reponame:SEDICI (UNLP)instname:Universidad Nacional de La Platainstacron:UNLP2025-09-29T11:18:18Zoai:sedici.unlp.edu.ar:10915/89180Institucionalhttp://sedici.unlp.edu.ar/Universidad públicaNo correspondehttp://sedici.unlp.edu.ar/oai/snrdalira@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:13292025-09-29 11:18:19.041SEDICI (UNLP) - Universidad Nacional de La Platafalse
dc.title.none.fl_str_mv Towards a Handwritten Text Interpretation Framework for Ancient Spanish Manuscripts
title Towards a Handwritten Text Interpretation Framework for Ancient Spanish Manuscripts
spellingShingle Towards a Handwritten Text Interpretation Framework for Ancient Spanish Manuscripts
Xamena, Eduardo
Ciencias Informáticas
Handwritten text recognition
Convolutional Neural Networks
Binarization
Document images
title_short Towards a Handwritten Text Interpretation Framework for Ancient Spanish Manuscripts
title_full Towards a Handwritten Text Interpretation Framework for Ancient Spanish Manuscripts
title_fullStr Towards a Handwritten Text Interpretation Framework for Ancient Spanish Manuscripts
title_full_unstemmed Towards a Handwritten Text Interpretation Framework for Ancient Spanish Manuscripts
title_sort Towards a Handwritten Text Interpretation Framework for Ancient Spanish Manuscripts
dc.creator.none.fl_str_mv Xamena, Eduardo
Orozco, Carlos Ismael
Carrasco Cabrera, Gastón
author Xamena, Eduardo
author_facet Xamena, Eduardo
Orozco, Carlos Ismael
Carrasco Cabrera, Gastón
author_role author
author2 Orozco, Carlos Ismael
Carrasco Cabrera, Gastón
author2_role author
author
dc.subject.none.fl_str_mv Ciencias Informáticas
Handwritten text recognition
Convolutional Neural Networks
Binarization
Document images
topic Ciencias Informáticas
Handwritten text recognition
Convolutional Neural Networks
Binarization
Document images
dc.description.none.fl_txt_mv Handwritten Text Recognition is an extensively studied research topic.We implement a widely known binarization method in order to preprocess handwritten text images efficiently and accurately, acquiring adequate binary black-white images for later recognition processes. Afterwards, the characters present in the documents are used to train and evaluate deep-learning mechanisms for the recognition task. Our framework provides good source images for the recognition phase in terms of noise removal and processing of low contrast images. Besides, the process of character recognition is also improved by means of deep-learning techniques.
Sociedad Argentina de Informática e Investigación Operativa
description Handwritten Text Recognition is an extensively studied research topic.We implement a widely known binarization method in order to preprocess handwritten text images efficiently and accurately, acquiring adequate binary black-white images for later recognition processes. Afterwards, the characters present in the documents are used to train and evaluate deep-learning mechanisms for the recognition task. Our framework provides good source images for the recognition phase in terms of noise removal and processing of low contrast images. Besides, the process of character recognition is also improved by means of deep-learning techniques.
publishDate 2019
dc.date.none.fl_str_mv 2019-09
dc.type.none.fl_str_mv info:eu-repo/semantics/conferenceObject
info:eu-repo/semantics/publishedVersion
Objeto de conferencia
http://purl.org/coar/resource_type/c_5794
info:ar-repo/semantics/documentoDeConferencia
format conferenceObject
status_str publishedVersion
dc.identifier.none.fl_str_mv http://sedici.unlp.edu.ar/handle/10915/89180
url http://sedici.unlp.edu.ar/handle/10915/89180
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/issn/2683-8990
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
http://creativecommons.org/licenses/by-nc-sa/3.0/
Creative Commons Attribution-NonCommercial-ShareAlike 3.0 Unported (CC BY-NC-SA 3.0)
eu_rights_str_mv openAccess
rights_invalid_str_mv http://creativecommons.org/licenses/by-nc-sa/3.0/
Creative Commons Attribution-NonCommercial-ShareAlike 3.0 Unported (CC BY-NC-SA 3.0)
dc.format.none.fl_str_mv application/pdf
28-34
dc.source.none.fl_str_mv reponame:SEDICI (UNLP)
instname:Universidad Nacional de La Plata
instacron:UNLP
reponame_str SEDICI (UNLP)
collection SEDICI (UNLP)
instname_str Universidad Nacional de La Plata
instacron_str UNLP
institution UNLP
repository.name.fl_str_mv SEDICI (UNLP) - Universidad Nacional de La Plata
repository.mail.fl_str_mv alira@sedici.unlp.edu.ar
_version_ 1844616056774066176
score 13.070432

Publicaciones similares