A GPU-Accelerated LPR Algorithm on Broad Vision Survillance Cameras

Autores
Dominguez, Leonardo Daniel; D'amato, Juan Pablo; Perez, Alejandro Julian; Rubiales, Aldo Jose
Año de publicación
2018
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
Video surveillance systems are employed to prevent crime, mounting hundreds of cameras and sensors monitoring activities during the whole day. Due to the huge amount of video information generated in real time, these surveillance centers are requiring more technology and intelligence to support human operators in many complex situations. There are important analyses that could be realized with this video-data: from criminalistics event detection to particular object recognition. One important tool is License Plate Recognition (LPR) that helps detecting vehicles that could have been robbed. Although corporative solutions exist, these techniques require a lot of processing power and special located cameras, that not always could be afford by the local government. In this context, the proposed project is based on applying open-source LPR algorithms that runs on already existent surveillance cameras. These cameras are observing a complete scene (not just a line as it is commonly used), so LPR algorithms are rather slow, processing only 1 image per second. For this reason, the objective is to improve the performance combining a parallel LPR running on graphic processor units (GPU) and object tracking algorithms. This work describes the ongoing implementation, the techniques currently used for object tracking and LPR implementation, and exposes results regarding the efficiency of the solution.
Fil: Dominguez, Leonardo Daniel. Universidad Nacional del Centro de la Provincia de Buenos Aires. Facultad de Ciencias Exactas. Grupo de Plasmas Densos Magnetizados. Provincia de Buenos Aires. Gobernación. Comision de Investigaciones Científicas. Grupo de Plasmas Densos Magnetizados; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tandil; Argentina
Fil: D'amato, Juan Pablo. Universidad Nacional del Centro de la Provincia de Buenos Aires. Facultad de Ciencias Exactas. Grupo de Plasmas Densos Magnetizados. Provincia de Buenos Aires. Gobernación. Comision de Investigaciones Científicas. Grupo de Plasmas Densos Magnetizados; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tandil; Argentina
Fil: Perez, Alejandro Julian. Universidad Nacional del Centro de la Provincia de Buenos Aires. Facultad de Ciencias Exactas. Grupo de Plasmas Densos Magnetizados. Provincia de Buenos Aires. Gobernación. Comision de Investigaciones Científicas. Grupo de Plasmas Densos Magnetizados; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tandil; Argentina. Provincia de Buenos Aires. Gobernación. Comisión de Investigaciones Científicas; Argentina
Fil: Rubiales, Aldo Jose. Universidad Nacional del Centro de la Provincia de Buenos Aires. Facultad de Ciencias Exactas. Grupo de Plasmas Densos Magnetizados. Provincia de Buenos Aires. Gobernación. Comision de Investigaciones Científicas. Grupo de Plasmas Densos Magnetizados; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tandil; Argentina. Provincia de Buenos Aires. Gobernación. Comisión de Investigaciones Científicas; Argentina
Materia
IMAGE PROCESSING
LICENSE-PLATE RECOGNITION
SURVEILLANCE
DIGITAL GOVERNMENT
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/111828
Acceder
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network_acronym_str CONICETDig
repository_id_str 3498
network_name_str CONICET Digital (CONICET)
spelling A GPU-Accelerated LPR Algorithm on Broad Vision Survillance CamerasDominguez, Leonardo DanielD'amato, Juan PabloPerez, Alejandro JulianRubiales, Aldo JoseIMAGE PROCESSINGLICENSE-PLATE RECOGNITIONSURVEILLANCEDIGITAL GOVERNMENThttps://purl.org/becyt/ford/1.2https://purl.org/becyt/ford/1Video surveillance systems are employed to prevent crime, mounting hundreds of cameras and sensors monitoring activities during the whole day. Due to the huge amount of video information generated in real time, these surveillance centers are requiring more technology and intelligence to support human operators in many complex situations. There are important analyses that could be realized with this video-data: from criminalistics event detection to particular object recognition. One important tool is License Plate Recognition (LPR) that helps detecting vehicles that could have been robbed. Although corporative solutions exist, these techniques require a lot of processing power and special located cameras, that not always could be afford by the local government. In this context, the proposed project is based on applying open-source LPR algorithms that runs on already existent surveillance cameras. These cameras are observing a complete scene (not just a line as it is commonly used), so LPR algorithms are rather slow, processing only 1 image per second. For this reason, the objective is to improve the performance combining a parallel LPR running on graphic processor units (GPU) and object tracking algorithms. This work describes the ongoing implementation, the techniques currently used for object tracking and LPR implementation, and exposes results regarding the efficiency of the solution.Fil: Dominguez, Leonardo Daniel. Universidad Nacional del Centro de la Provincia de Buenos Aires. Facultad de Ciencias Exactas. Grupo de Plasmas Densos Magnetizados. Provincia de Buenos Aires. Gobernación. Comision de Investigaciones Científicas. Grupo de Plasmas Densos Magnetizados; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tandil; ArgentinaFil: D'amato, Juan Pablo. Universidad Nacional del Centro de la Provincia de Buenos Aires. Facultad de Ciencias Exactas. Grupo de Plasmas Densos Magnetizados. Provincia de Buenos Aires. Gobernación. Comision de Investigaciones Científicas. Grupo de Plasmas Densos Magnetizados; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tandil; ArgentinaFil: Perez, Alejandro Julian. Universidad Nacional del Centro de la Provincia de Buenos Aires. Facultad de Ciencias Exactas. Grupo de Plasmas Densos Magnetizados. Provincia de Buenos Aires. Gobernación. Comision de Investigaciones Científicas. Grupo de Plasmas Densos Magnetizados; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tandil; Argentina. Provincia de Buenos Aires. Gobernación. Comisión de Investigaciones Científicas; ArgentinaFil: Rubiales, Aldo Jose. Universidad Nacional del Centro de la Provincia de Buenos Aires. Facultad de Ciencias Exactas. Grupo de Plasmas Densos Magnetizados. Provincia de Buenos Aires. Gobernación. Comision de Investigaciones Científicas. Grupo de Plasmas Densos Magnetizados; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tandil; Argentina. Provincia de Buenos Aires. Gobernación. Comisión de Investigaciones Científicas; ArgentinaIberian Association for Information Systems and Technologies2018-07info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfapplication/pdfapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/111828Dominguez, Leonardo Daniel; D'amato, Juan Pablo; Perez, Alejandro Julian; Rubiales, Aldo Jose; A GPU-Accelerated LPR Algorithm on Broad Vision Survillance Cameras; Iberian Association for Information Systems and Technologies; European Journal of Sustainable Development Research; 3; 7-2018; 1-72468-4376CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/url/https://www.jisem-journal.com/article/a-gpu-accelerated-lpr-algorithm-on-broad-vision-survillance-camerasinfo:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-03T09:53:13Zoai:ri.conicet.gov.ar:11336/111828instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982025-09-03 09:53:13.311CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv A GPU-Accelerated LPR Algorithm on Broad Vision Survillance Cameras
title A GPU-Accelerated LPR Algorithm on Broad Vision Survillance Cameras
spellingShingle A GPU-Accelerated LPR Algorithm on Broad Vision Survillance Cameras
Dominguez, Leonardo Daniel
IMAGE PROCESSING
LICENSE-PLATE RECOGNITION
SURVEILLANCE
DIGITAL GOVERNMENT
title_short A GPU-Accelerated LPR Algorithm on Broad Vision Survillance Cameras
title_full A GPU-Accelerated LPR Algorithm on Broad Vision Survillance Cameras
title_fullStr A GPU-Accelerated LPR Algorithm on Broad Vision Survillance Cameras
title_full_unstemmed A GPU-Accelerated LPR Algorithm on Broad Vision Survillance Cameras
title_sort A GPU-Accelerated LPR Algorithm on Broad Vision Survillance Cameras
dc.creator.none.fl_str_mv Dominguez, Leonardo Daniel
D'amato, Juan Pablo
Perez, Alejandro Julian
Rubiales, Aldo Jose
author Dominguez, Leonardo Daniel
author_facet Dominguez, Leonardo Daniel
D'amato, Juan Pablo
Perez, Alejandro Julian
Rubiales, Aldo Jose
author_role author
author2 D'amato, Juan Pablo
Perez, Alejandro Julian
Rubiales, Aldo Jose
author2_role author
author
author
dc.subject.none.fl_str_mv IMAGE PROCESSING
LICENSE-PLATE RECOGNITION
SURVEILLANCE
DIGITAL GOVERNMENT
topic IMAGE PROCESSING
LICENSE-PLATE RECOGNITION
SURVEILLANCE
DIGITAL GOVERNMENT
purl_subject.fl_str_mv https://purl.org/becyt/ford/1.2
https://purl.org/becyt/ford/1
dc.description.none.fl_txt_mv Video surveillance systems are employed to prevent crime, mounting hundreds of cameras and sensors monitoring activities during the whole day. Due to the huge amount of video information generated in real time, these surveillance centers are requiring more technology and intelligence to support human operators in many complex situations. There are important analyses that could be realized with this video-data: from criminalistics event detection to particular object recognition. One important tool is License Plate Recognition (LPR) that helps detecting vehicles that could have been robbed. Although corporative solutions exist, these techniques require a lot of processing power and special located cameras, that not always could be afford by the local government. In this context, the proposed project is based on applying open-source LPR algorithms that runs on already existent surveillance cameras. These cameras are observing a complete scene (not just a line as it is commonly used), so LPR algorithms are rather slow, processing only 1 image per second. For this reason, the objective is to improve the performance combining a parallel LPR running on graphic processor units (GPU) and object tracking algorithms. This work describes the ongoing implementation, the techniques currently used for object tracking and LPR implementation, and exposes results regarding the efficiency of the solution.
Fil: Dominguez, Leonardo Daniel. Universidad Nacional del Centro de la Provincia de Buenos Aires. Facultad de Ciencias Exactas. Grupo de Plasmas Densos Magnetizados. Provincia de Buenos Aires. Gobernación. Comision de Investigaciones Científicas. Grupo de Plasmas Densos Magnetizados; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tandil; Argentina
Fil: D'amato, Juan Pablo. Universidad Nacional del Centro de la Provincia de Buenos Aires. Facultad de Ciencias Exactas. Grupo de Plasmas Densos Magnetizados. Provincia de Buenos Aires. Gobernación. Comision de Investigaciones Científicas. Grupo de Plasmas Densos Magnetizados; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tandil; Argentina
Fil: Perez, Alejandro Julian. Universidad Nacional del Centro de la Provincia de Buenos Aires. Facultad de Ciencias Exactas. Grupo de Plasmas Densos Magnetizados. Provincia de Buenos Aires. Gobernación. Comision de Investigaciones Científicas. Grupo de Plasmas Densos Magnetizados; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tandil; Argentina. Provincia de Buenos Aires. Gobernación. Comisión de Investigaciones Científicas; Argentina
Fil: Rubiales, Aldo Jose. Universidad Nacional del Centro de la Provincia de Buenos Aires. Facultad de Ciencias Exactas. Grupo de Plasmas Densos Magnetizados. Provincia de Buenos Aires. Gobernación. Comision de Investigaciones Científicas. Grupo de Plasmas Densos Magnetizados; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tandil; Argentina. Provincia de Buenos Aires. Gobernación. Comisión de Investigaciones Científicas; Argentina
description Video surveillance systems are employed to prevent crime, mounting hundreds of cameras and sensors monitoring activities during the whole day. Due to the huge amount of video information generated in real time, these surveillance centers are requiring more technology and intelligence to support human operators in many complex situations. There are important analyses that could be realized with this video-data: from criminalistics event detection to particular object recognition. One important tool is License Plate Recognition (LPR) that helps detecting vehicles that could have been robbed. Although corporative solutions exist, these techniques require a lot of processing power and special located cameras, that not always could be afford by the local government. In this context, the proposed project is based on applying open-source LPR algorithms that runs on already existent surveillance cameras. These cameras are observing a complete scene (not just a line as it is commonly used), so LPR algorithms are rather slow, processing only 1 image per second. For this reason, the objective is to improve the performance combining a parallel LPR running on graphic processor units (GPU) and object tracking algorithms. This work describes the ongoing implementation, the techniques currently used for object tracking and LPR implementation, and exposes results regarding the efficiency of the solution.
publishDate 2018
dc.date.none.fl_str_mv 2018-07
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/11336/111828
Dominguez, Leonardo Daniel; D'amato, Juan Pablo; Perez, Alejandro Julian; Rubiales, Aldo Jose; A GPU-Accelerated LPR Algorithm on Broad Vision Survillance Cameras; Iberian Association for Information Systems and Technologies; European Journal of Sustainable Development Research; 3; 7-2018; 1-7
2468-4376
CONICET Digital
CONICET
url http://hdl.handle.net/11336/111828
identifier_str_mv Dominguez, Leonardo Daniel; D'amato, Juan Pablo; Perez, Alejandro Julian; Rubiales, Aldo Jose; A GPU-Accelerated LPR Algorithm on Broad Vision Survillance Cameras; Iberian Association for Information Systems and Technologies; European Journal of Sustainable Development Research; 3; 7-2018; 1-7
2468-4376
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/url/https://www.jisem-journal.com/article/a-gpu-accelerated-lpr-algorithm-on-broad-vision-survillance-cameras
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
application/pdf
application/pdf
application/pdf
dc.publisher.none.fl_str_mv Iberian Association for Information Systems and Technologies
publisher.none.fl_str_mv Iberian Association for Information Systems and Technologies
dc.source.none.fl_str_mv reponame:CONICET Digital (CONICET)
instname:Consejo Nacional de Investigaciones Científicas y Técnicas
reponame_str CONICET Digital (CONICET)
collection CONICET Digital (CONICET)
instname_str Consejo Nacional de Investigaciones Científicas y Técnicas
repository.name.fl_str_mv CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas
repository.mail.fl_str_mv dasensio@conicet.gov.ar; lcarlino@conicet.gov.ar
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score 13.13397

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