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...

Full description

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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spelling 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
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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
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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
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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
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