Manuscript document digitalization and recognition: a first approach
- Autores
- De Giusti, Marisa Raquel; Vila, María Marta; Villarreal, Gonzalo Luján
- Año de publicación
- 2005
- Idioma
- inglés
- Tipo de recurso
- artículo
- Estado
- versión enviada
- Descripción
- The handwritten manuscript recognizing process belongs to a set of initiatives which lean to the preservation of cultural patrimony gathered in libraries and archives, where there exist a great wealth in documents and even handwritten cards that accompany incunabula books. This work is the starting point of a research and development project oriented to digitalization and recognition of manuscript materials. The paper presented here discuss different algorithms used in the first stage dedicated to image noise-cleaning in order to improve it before the character recognition process begins. In order to make the handwritten-text recognition and image digitalization process efficient, it must be preceded by a preprocessing stage of the image to be treated, which includes thresholding, noise cleaning, thinning, base-line alignment and image segmentation, among others. Each of these steps will allow us to reduce the injurious variability when recognizing manuscripts (noise, random gray levels, slanted characters, ink level in different zones), and so increasing the probability of obtaining a suitable text recognition. In this paper, two image thinning methods are considered, and implemented. Finally, an evaluation is carried out obtaining many conclusions related to efficiency, speed and requirements, as well as ideas for future implementations.
- Materia
-
Ciencias de la Computación e Información
digitalización
Image processing software
conservación patrimonial - Nivel de accesibilidad
- acceso abierto
- Condiciones de uso
- http://creativecommons.org/licenses/by/4.0/
- Repositorio
- Institución
- Comisión de Investigaciones Científicas de la Provincia de Buenos Aires
- OAI Identificador
- oai:digital.cic.gba.gob.ar:11746/3826
Ver los metadatos del registro completo
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spelling |
Manuscript document digitalization and recognition: a first approachDe Giusti, Marisa RaquelVila, María MartaVillarreal, Gonzalo LujánCiencias de la Computación e InformacióndigitalizaciónImage processing softwareconservación patrimonialThe handwritten manuscript recognizing process belongs to a set of initiatives which lean to the preservation of cultural patrimony gathered in libraries and archives, where there exist a great wealth in documents and even handwritten cards that accompany incunabula books. This work is the starting point of a research and development project oriented to digitalization and recognition of manuscript materials. The paper presented here discuss different algorithms used in the first stage dedicated to image noise-cleaning in order to improve it before the character recognition process begins. In order to make the handwritten-text recognition and image digitalization process efficient, it must be preceded by a preprocessing stage of the image to be treated, which includes thresholding, noise cleaning, thinning, base-line alignment and image segmentation, among others. Each of these steps will allow us to reduce the injurious variability when recognizing manuscripts (noise, random gray levels, slanted characters, ink level in different zones), and so increasing the probability of obtaining a suitable text recognition. In this paper, two image thinning methods are considered, and implemented. Finally, an evaluation is carried out obtaining many conclusions related to efficiency, speed and requirements, as well as ideas for future implementations.2005-10-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/submittedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfhttps://digital.cic.gba.gob.ar/handle/11746/3826enginfo:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by/4.0/reponame:CIC Digital (CICBA)instname:Comisión de Investigaciones Científicas de la Provincia de Buenos Airesinstacron:CICBA2025-09-29T13:40:23Zoai:digital.cic.gba.gob.ar:11746/3826Institucionalhttp://digital.cic.gba.gob.arOrganismo científico-tecnológicoNo correspondehttp://digital.cic.gba.gob.ar/oai/snrdmarisa.degiusti@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:94412025-09-29 13:40:24.101CIC Digital (CICBA) - Comisión de Investigaciones Científicas de la Provincia de Buenos Airesfalse |
dc.title.none.fl_str_mv |
Manuscript document digitalization and recognition: a first approach |
title |
Manuscript document digitalization and recognition: a first approach |
spellingShingle |
Manuscript document digitalization and recognition: a first approach De Giusti, Marisa Raquel Ciencias de la Computación e Información digitalización Image processing software conservación patrimonial |
title_short |
Manuscript document digitalization and recognition: a first approach |
title_full |
Manuscript document digitalization and recognition: a first approach |
title_fullStr |
Manuscript document digitalization and recognition: a first approach |
title_full_unstemmed |
Manuscript document digitalization and recognition: a first approach |
title_sort |
Manuscript document digitalization and recognition: a first approach |
dc.creator.none.fl_str_mv |
De Giusti, Marisa Raquel Vila, María Marta Villarreal, Gonzalo Luján |
author |
De Giusti, Marisa Raquel |
author_facet |
De Giusti, Marisa Raquel Vila, María Marta Villarreal, Gonzalo Luján |
author_role |
author |
author2 |
Vila, María Marta Villarreal, Gonzalo Luján |
author2_role |
author author |
dc.subject.none.fl_str_mv |
Ciencias de la Computación e Información digitalización Image processing software conservación patrimonial |
topic |
Ciencias de la Computación e Información digitalización Image processing software conservación patrimonial |
dc.description.none.fl_txt_mv |
The handwritten manuscript recognizing process belongs to a set of initiatives which lean to the preservation of cultural patrimony gathered in libraries and archives, where there exist a great wealth in documents and even handwritten cards that accompany incunabula books. This work is the starting point of a research and development project oriented to digitalization and recognition of manuscript materials. The paper presented here discuss different algorithms used in the first stage dedicated to image noise-cleaning in order to improve it before the character recognition process begins. In order to make the handwritten-text recognition and image digitalization process efficient, it must be preceded by a preprocessing stage of the image to be treated, which includes thresholding, noise cleaning, thinning, base-line alignment and image segmentation, among others. Each of these steps will allow us to reduce the injurious variability when recognizing manuscripts (noise, random gray levels, slanted characters, ink level in different zones), and so increasing the probability of obtaining a suitable text recognition. In this paper, two image thinning methods are considered, and implemented. Finally, an evaluation is carried out obtaining many conclusions related to efficiency, speed and requirements, as well as ideas for future implementations. |
description |
The handwritten manuscript recognizing process belongs to a set of initiatives which lean to the preservation of cultural patrimony gathered in libraries and archives, where there exist a great wealth in documents and even handwritten cards that accompany incunabula books. This work is the starting point of a research and development project oriented to digitalization and recognition of manuscript materials. The paper presented here discuss different algorithms used in the first stage dedicated to image noise-cleaning in order to improve it before the character recognition process begins. In order to make the handwritten-text recognition and image digitalization process efficient, it must be preceded by a preprocessing stage of the image to be treated, which includes thresholding, noise cleaning, thinning, base-line alignment and image segmentation, among others. Each of these steps will allow us to reduce the injurious variability when recognizing manuscripts (noise, random gray levels, slanted characters, ink level in different zones), and so increasing the probability of obtaining a suitable text recognition. In this paper, two image thinning methods are considered, and implemented. Finally, an evaluation is carried out obtaining many conclusions related to efficiency, speed and requirements, as well as ideas for future implementations. |
publishDate |
2005 |
dc.date.none.fl_str_mv |
2005-10-01 |
dc.type.none.fl_str_mv |
info:eu-repo/semantics/article info:eu-repo/semantics/submittedVersion http://purl.org/coar/resource_type/c_6501 info:ar-repo/semantics/articulo |
format |
article |
status_str |
submittedVersion |
dc.identifier.none.fl_str_mv |
https://digital.cic.gba.gob.ar/handle/11746/3826 |
url |
https://digital.cic.gba.gob.ar/handle/11746/3826 |
dc.language.none.fl_str_mv |
eng |
language |
eng |
dc.rights.none.fl_str_mv |
info:eu-repo/semantics/openAccess http://creativecommons.org/licenses/by/4.0/ |
eu_rights_str_mv |
openAccess |
rights_invalid_str_mv |
http://creativecommons.org/licenses/by/4.0/ |
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application/pdf |
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reponame:CIC Digital (CICBA) instname:Comisión de Investigaciones Científicas de la Provincia de Buenos Aires instacron:CICBA |
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CIC Digital (CICBA) |
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CIC Digital (CICBA) |
instname_str |
Comisión de Investigaciones Científicas de la Provincia de Buenos Aires |
instacron_str |
CICBA |
institution |
CICBA |
repository.name.fl_str_mv |
CIC Digital (CICBA) - Comisión de Investigaciones Científicas de la Provincia de Buenos Aires |
repository.mail.fl_str_mv |
marisa.degiusti@sedici.unlp.edu.ar |
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13.069144 |