FPGA-based translation system from colombian sign language to text
This paper presents the development of a system aimed to facilitate the communication and interaction of people with severe hearing impairment with other people. The system employs artificial vision techniques to the recognition of static signs of Colombian Sign Language (LSC). The system has four s...
- Autores:
-
Guerrero Balaguera, Juan David
Pérez Holguín, Wilson Javier
- Tipo de recurso:
- Article of journal
- Fecha de publicación:
- 2015
- Institución:
- Universidad Nacional de Colombia
- Repositorio:
- Universidad Nacional de Colombia
- Idioma:
- spa
- OAI Identifier:
- oai:repositorio.unal.edu.co:unal/60779
- Acceso en línea:
- https://repositorio.unal.edu.co/handle/unal/60779
http://bdigital.unal.edu.co/59111/
- Palabra clave:
- 62 Ingeniería y operaciones afines / Engineering
FPGA
Lengua de Señas Colombiana (LSC)
Procesamiento de Imágenes
Reconocimiento de Lengua de Señas
Redes Neuronales Artificiales
- Rights
- openAccess
- License
- Atribución-NoComercial 4.0 Internacional
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Atribución-NoComercial 4.0 InternacionalDerechos reservados - Universidad Nacional de Colombiahttp://creativecommons.org/licenses/by-nc/4.0/info:eu-repo/semantics/openAccesshttp://purl.org/coar/access_right/c_abf2Guerrero Balaguera, Juan David943dee65-ad21-4f51-8855-4c52a234ecba300Pérez Holguín, Wilson Javierf063b4c2-6633-46c6-aff7-cec5ef262e493002019-07-02T19:05:40Z2019-07-02T19:05:40Z2015-01-01ISSN: 2346-2183https://repositorio.unal.edu.co/handle/unal/60779http://bdigital.unal.edu.co/59111/This paper presents the development of a system aimed to facilitate the communication and interaction of people with severe hearing impairment with other people. The system employs artificial vision techniques to the recognition of static signs of Colombian Sign Language (LSC). The system has four stages: Image capture, preprocessing, feature extraction and recognition. The image is captured by a digital camera TRDB-D5M for Altera’s DE1 and DE2 development boards. In the preprocessing stage, the sign is extracted from the background of the image using the thresholding segmentation method; then, the segmented image is filtered using a morphological operation to remove the noise. The feature extraction stage is based on the creation of two vectors to characterize the shape of the hand used to make the sign. The recognition stage is made up a multilayer perceptron neural network (MLP), which functions as a classifier. The system was implemented in the Altera’s Cyclone II FPGA EP2C70F896C6 device and does not require the use of gloves or visual markers for its proper operation. The results show that the system is able to recognize all the 23 signs of the LSC with a recognition rate of 98.15 %.application/pdfspaUniversidad Nacional de Colombia (Sede Medellín). Facultad de Minas.https://revistas.unal.edu.co/index.php/dyna/article/view/43075Universidad Nacional de Colombia Revistas electrónicas UN DynaDynaGuerrero Balaguera, Juan David and Pérez Holguín, Wilson Javier (2015) FPGA-based translation system from colombian sign language to text. DYNA, 82 (189). pp. 172-181. ISSN 2346-218362 Ingeniería y operaciones afines / EngineeringFPGALengua de Señas Colombiana (LSC)Procesamiento de ImágenesReconocimiento de Lengua de SeñasRedes Neuronales ArtificialesFPGA-based translation system from colombian sign language to textArtículo de revistainfo:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501http://purl.org/coar/resource_type/c_2df8fbb1http://purl.org/coar/version/c_970fb48d4fbd8a85Texthttp://purl.org/redcol/resource_type/ARTORIGINAL43075-240413-1-PB.pdfapplication/pdf1728996https://repositorio.unal.edu.co/bitstream/unal/60779/1/43075-240413-1-PB.pdf20e12eba824d4e4d8de84d9a5e70bc5dMD51THUMBNAIL43075-240413-1-PB.pdf.jpg43075-240413-1-PB.pdf.jpgGenerated Thumbnailimage/jpeg9193https://repositorio.unal.edu.co/bitstream/unal/60779/2/43075-240413-1-PB.pdf.jpgb0d855462168d8ad1d514f72b22d07b0MD52unal/60779oai:repositorio.unal.edu.co:unal/607792024-04-15 23:08:44.037Repositorio Institucional Universidad Nacional de Colombiarepositorio_nal@unal.edu.co |
dc.title.spa.fl_str_mv |
FPGA-based translation system from colombian sign language to text |
title |
FPGA-based translation system from colombian sign language to text |
spellingShingle |
FPGA-based translation system from colombian sign language to text 62 Ingeniería y operaciones afines / Engineering FPGA Lengua de Señas Colombiana (LSC) Procesamiento de Imágenes Reconocimiento de Lengua de Señas Redes Neuronales Artificiales |
title_short |
FPGA-based translation system from colombian sign language to text |
title_full |
FPGA-based translation system from colombian sign language to text |
title_fullStr |
FPGA-based translation system from colombian sign language to text |
title_full_unstemmed |
FPGA-based translation system from colombian sign language to text |
title_sort |
FPGA-based translation system from colombian sign language to text |
dc.creator.fl_str_mv |
Guerrero Balaguera, Juan David Pérez Holguín, Wilson Javier |
dc.contributor.author.spa.fl_str_mv |
Guerrero Balaguera, Juan David Pérez Holguín, Wilson Javier |
dc.subject.ddc.spa.fl_str_mv |
62 Ingeniería y operaciones afines / Engineering |
topic |
62 Ingeniería y operaciones afines / Engineering FPGA Lengua de Señas Colombiana (LSC) Procesamiento de Imágenes Reconocimiento de Lengua de Señas Redes Neuronales Artificiales |
dc.subject.proposal.spa.fl_str_mv |
FPGA Lengua de Señas Colombiana (LSC) Procesamiento de Imágenes Reconocimiento de Lengua de Señas Redes Neuronales Artificiales |
description |
This paper presents the development of a system aimed to facilitate the communication and interaction of people with severe hearing impairment with other people. The system employs artificial vision techniques to the recognition of static signs of Colombian Sign Language (LSC). The system has four stages: Image capture, preprocessing, feature extraction and recognition. The image is captured by a digital camera TRDB-D5M for Altera’s DE1 and DE2 development boards. In the preprocessing stage, the sign is extracted from the background of the image using the thresholding segmentation method; then, the segmented image is filtered using a morphological operation to remove the noise. The feature extraction stage is based on the creation of two vectors to characterize the shape of the hand used to make the sign. The recognition stage is made up a multilayer perceptron neural network (MLP), which functions as a classifier. The system was implemented in the Altera’s Cyclone II FPGA EP2C70F896C6 device and does not require the use of gloves or visual markers for its proper operation. The results show that the system is able to recognize all the 23 signs of the LSC with a recognition rate of 98.15 %. |
publishDate |
2015 |
dc.date.issued.spa.fl_str_mv |
2015-01-01 |
dc.date.accessioned.spa.fl_str_mv |
2019-07-02T19:05:40Z |
dc.date.available.spa.fl_str_mv |
2019-07-02T19:05:40Z |
dc.type.spa.fl_str_mv |
Artículo de revista |
dc.type.coar.fl_str_mv |
http://purl.org/coar/resource_type/c_2df8fbb1 |
dc.type.driver.spa.fl_str_mv |
info:eu-repo/semantics/article |
dc.type.version.spa.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.coar.spa.fl_str_mv |
http://purl.org/coar/resource_type/c_6501 |
dc.type.coarversion.spa.fl_str_mv |
http://purl.org/coar/version/c_970fb48d4fbd8a85 |
dc.type.content.spa.fl_str_mv |
Text |
dc.type.redcol.spa.fl_str_mv |
http://purl.org/redcol/resource_type/ART |
format |
http://purl.org/coar/resource_type/c_6501 |
status_str |
publishedVersion |
dc.identifier.issn.spa.fl_str_mv |
ISSN: 2346-2183 |
dc.identifier.uri.none.fl_str_mv |
https://repositorio.unal.edu.co/handle/unal/60779 |
dc.identifier.eprints.spa.fl_str_mv |
http://bdigital.unal.edu.co/59111/ |
identifier_str_mv |
ISSN: 2346-2183 |
url |
https://repositorio.unal.edu.co/handle/unal/60779 http://bdigital.unal.edu.co/59111/ |
dc.language.iso.spa.fl_str_mv |
spa |
language |
spa |
dc.relation.spa.fl_str_mv |
https://revistas.unal.edu.co/index.php/dyna/article/view/43075 |
dc.relation.ispartof.spa.fl_str_mv |
Universidad Nacional de Colombia Revistas electrónicas UN Dyna Dyna |
dc.relation.references.spa.fl_str_mv |
Guerrero Balaguera, Juan David and Pérez Holguín, Wilson Javier (2015) FPGA-based translation system from colombian sign language to text. DYNA, 82 (189). pp. 172-181. ISSN 2346-2183 |
dc.rights.spa.fl_str_mv |
Derechos reservados - Universidad Nacional de Colombia |
dc.rights.coar.fl_str_mv |
http://purl.org/coar/access_right/c_abf2 |
dc.rights.license.spa.fl_str_mv |
Atribución-NoComercial 4.0 Internacional |
dc.rights.uri.spa.fl_str_mv |
http://creativecommons.org/licenses/by-nc/4.0/ |
dc.rights.accessrights.spa.fl_str_mv |
info:eu-repo/semantics/openAccess |
rights_invalid_str_mv |
Atribución-NoComercial 4.0 Internacional Derechos reservados - Universidad Nacional de Colombia http://creativecommons.org/licenses/by-nc/4.0/ http://purl.org/coar/access_right/c_abf2 |
eu_rights_str_mv |
openAccess |
dc.format.mimetype.spa.fl_str_mv |
application/pdf |
dc.publisher.spa.fl_str_mv |
Universidad Nacional de Colombia (Sede Medellín). Facultad de Minas. |
institution |
Universidad Nacional de Colombia |
bitstream.url.fl_str_mv |
https://repositorio.unal.edu.co/bitstream/unal/60779/1/43075-240413-1-PB.pdf https://repositorio.unal.edu.co/bitstream/unal/60779/2/43075-240413-1-PB.pdf.jpg |
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