Classification of artificial light sources and estimation of Color Rendering Index using RGB sensors, K Nearest Neighbor and Radial Basis Function

ABSTRACT: Three types of artificial light sources work with electricity: incandescent, fluorescent and LED. These sources require characterization processes to allow selecting the most suitable for the application, to evaluate their capacity or more recently to tune and adjust their replicability us...

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Autores:
Vargas Bonilla, Jesús Francisco
Botero Valencia, Juan Sebastián
López Giraldo, Francisco Eugenio
Tipo de recurso:
Article of investigation
Fecha de publicación:
2015
Institución:
Universidad de Antioquia
Repositorio:
Repositorio UdeA
Idioma:
eng
OAI Identifier:
oai:bibliotecadigital.udea.edu.co:10495/38444
Acceso en línea:
https://hdl.handle.net/10495/38444
Palabra clave:
Fuentes luminosas
Light sources
Sensores
Sensors
Índice de reproducción cromática
Color Rendering Index
http://aims.fao.org/aos/agrovoc/c_28279
Rights
openAccess
License
http://creativecommons.org/licenses/by-nc-nd/2.5/co/
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oai_identifier_str oai:bibliotecadigital.udea.edu.co:10495/38444
network_acronym_str UDEA2
network_name_str Repositorio UdeA
repository_id_str
dc.title.spa.fl_str_mv Classification of artificial light sources and estimation of Color Rendering Index using RGB sensors, K Nearest Neighbor and Radial Basis Function
title Classification of artificial light sources and estimation of Color Rendering Index using RGB sensors, K Nearest Neighbor and Radial Basis Function
spellingShingle Classification of artificial light sources and estimation of Color Rendering Index using RGB sensors, K Nearest Neighbor and Radial Basis Function
Fuentes luminosas
Light sources
Sensores
Sensors
Índice de reproducción cromática
Color Rendering Index
http://aims.fao.org/aos/agrovoc/c_28279
title_short Classification of artificial light sources and estimation of Color Rendering Index using RGB sensors, K Nearest Neighbor and Radial Basis Function
title_full Classification of artificial light sources and estimation of Color Rendering Index using RGB sensors, K Nearest Neighbor and Radial Basis Function
title_fullStr Classification of artificial light sources and estimation of Color Rendering Index using RGB sensors, K Nearest Neighbor and Radial Basis Function
title_full_unstemmed Classification of artificial light sources and estimation of Color Rendering Index using RGB sensors, K Nearest Neighbor and Radial Basis Function
title_sort Classification of artificial light sources and estimation of Color Rendering Index using RGB sensors, K Nearest Neighbor and Radial Basis Function
dc.creator.fl_str_mv Vargas Bonilla, Jesús Francisco
Botero Valencia, Juan Sebastián
López Giraldo, Francisco Eugenio
dc.contributor.author.none.fl_str_mv Vargas Bonilla, Jesús Francisco
Botero Valencia, Juan Sebastián
López Giraldo, Francisco Eugenio
dc.contributor.researchgroup.spa.fl_str_mv Sistemas Embebidos e Inteligencia Computacional (SISTEMIC)
dc.subject.lemb.none.fl_str_mv Fuentes luminosas
Light sources
topic Fuentes luminosas
Light sources
Sensores
Sensors
Índice de reproducción cromática
Color Rendering Index
http://aims.fao.org/aos/agrovoc/c_28279
dc.subject.agrovoc.none.fl_str_mv Sensores
Sensors
dc.subject.proposal.spa.fl_str_mv Índice de reproducción cromática
Color Rendering Index
dc.subject.agrovocuri.none.fl_str_mv http://aims.fao.org/aos/agrovoc/c_28279
description ABSTRACT: Three types of artificial light sources work with electricity: incandescent, fluorescent and LED. These sources require characterization processes to allow selecting the most suitable for the application, to evaluate their capacity or more recently to tune and adjust their replicability using control algorithms. Therefore, it has been necessary to develop indices that represent these capabilities. The Color Rendering Index (CRI) is a measure used to characterize the color reproducibility of a light source in comparison to an ideal light source. The Correlated Color Temperature (CCT) is used to characterize light sources by representing the color as the temperature of a black body in Kelvin that shows nearly the same chromaticity as the analyzed light source. Using spectral information to determine the values in the XYZ space and deriving the calculation described in the standard is the best way to estimate the value of the CCT and the CRI. In this work, we implement a method to classify light sources and to select an estimation model of the CRI and the CCT using a low cost RGB sensor. The model estimation has been developed in this work and a separated algorithm for each source type has been built. The results show that using a K-Nearest Neighbor classifier, the error resulted less than $3.6%$. The error of the model estimation for the LED was 1.8%, for fluorescent light sources 0.09% and 1.2% for incandescent light sources.
publishDate 2015
dc.date.issued.none.fl_str_mv 2015
dc.date.accessioned.none.fl_str_mv 2024-03-03T17:18:34Z
dc.date.available.none.fl_str_mv 2024-03-03T17:18:34Z
dc.type.spa.fl_str_mv Artículo de investigación
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dc.identifier.uri.none.fl_str_mv https://hdl.handle.net/10495/38444
dc.identifier.doi.none.fl_str_mv 10.21307/ijssis-2017-817
dc.identifier.eissn.none.fl_str_mv 1178-5608
url https://hdl.handle.net/10495/38444
identifier_str_mv 10.21307/ijssis-2017-817
1178-5608
dc.language.iso.spa.fl_str_mv eng
language eng
dc.relation.citationendpage.spa.fl_str_mv 1520
dc.relation.citationissue.spa.fl_str_mv 3
dc.relation.citationstartpage.spa.fl_str_mv 1505
dc.relation.citationvolume.spa.fl_str_mv 8
dc.relation.ispartofjournal.spa.fl_str_mv International Journal on Smart Sensing and Intelligent Systems
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dc.format.extent.spa.fl_str_mv 20 páginas
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dc.publisher.spa.fl_str_mv Sciendo
dc.publisher.place.spa.fl_str_mv Nueva Zelanda
institution Universidad de Antioquia
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spelling Vargas Bonilla, Jesús FranciscoBotero Valencia, Juan SebastiánLópez Giraldo, Francisco EugenioSistemas Embebidos e Inteligencia Computacional (SISTEMIC)2024-03-03T17:18:34Z2024-03-03T17:18:34Z2015https://hdl.handle.net/10495/3844410.21307/ijssis-2017-8171178-5608ABSTRACT: Three types of artificial light sources work with electricity: incandescent, fluorescent and LED. These sources require characterization processes to allow selecting the most suitable for the application, to evaluate their capacity or more recently to tune and adjust their replicability using control algorithms. Therefore, it has been necessary to develop indices that represent these capabilities. The Color Rendering Index (CRI) is a measure used to characterize the color reproducibility of a light source in comparison to an ideal light source. The Correlated Color Temperature (CCT) is used to characterize light sources by representing the color as the temperature of a black body in Kelvin that shows nearly the same chromaticity as the analyzed light source. Using spectral information to determine the values in the XYZ space and deriving the calculation described in the standard is the best way to estimate the value of the CCT and the CRI. In this work, we implement a method to classify light sources and to select an estimation model of the CRI and the CCT using a low cost RGB sensor. The model estimation has been developed in this work and a separated algorithm for each source type has been built. The results show that using a K-Nearest Neighbor classifier, the error resulted less than $3.6%$. The error of the model estimation for the LED was 1.8%, for fluorescent light sources 0.09% and 1.2% for incandescent light sources.COL001071720 páginasapplication/pdfengSciendoNueva Zelandahttp://creativecommons.org/licenses/by-nc-nd/2.5/co/https://creativecommons.org/licenses/by-nc-nd/4.0/info:eu-repo/semantics/openAccesshttp://purl.org/coar/access_right/c_abf2Classification of artificial light sources and estimation of Color Rendering Index using RGB sensors, K Nearest Neighbor and Radial Basis FunctionArtículo de investigaciónhttp://purl.org/coar/resource_type/c_2df8fbb1https://purl.org/redcol/resource_type/ARThttp://purl.org/coar/version/c_970fb48d4fbd8a85info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionFuentes luminosasLight sourcesSensoresSensorsÍndice de reproducción cromáticaColor Rendering Indexhttp://aims.fao.org/aos/agrovoc/c_282791520315058International Journal on Smart Sensing and Intelligent SystemsPublicationORIGINALVargasJesus_2015_ClassificationArtificialLight.pdfVargasJesus_2015_ClassificationArtificialLight.pdfArtículo de investigaciónapplication/pdf1738594https://bibliotecadigital.udea.edu.co/bitstreams/813f9a8b-54f7-4bd1-9fd9-121ef527cc20/download2a05b9ae2ed508df0d006eb997f0cd78MD51trueAnonymousREADCC-LICENSElicense_rdflicense_rdfapplication/rdf+xml; charset=utf-8823https://bibliotecadigital.udea.edu.co/bitstreams/0bd4f0fd-1f82-405d-bd9a-c739985d20a9/downloadb88b088d9957e670ce3b3fbe2eedbc13MD52falseAnonymousREADLICENSElicense.txtlicense.txttext/plain; charset=utf-81748https://bibliotecadigital.udea.edu.co/bitstreams/a322c9a0-96a4-46ea-af51-8d94c93d7668/download8a4605be74aa9ea9d79846c1fba20a33MD53falseAnonymousREADTEXTVargasJesus_2015_ClassificationArtificialLight.pdf.txtVargasJesus_2015_ClassificationArtificialLight.pdf.txtExtracted texttext/plain36801https://bibliotecadigital.udea.edu.co/bitstreams/9da7c8bc-88b7-4fcb-ab22-0905dff551ca/download7e418eaee9143e983527c4f07a23d679MD56falseAnonymousREADTHUMBNAILVargasJesus_2015_ClassificationArtificialLight.pdf.jpgVargasJesus_2015_ClassificationArtificialLight.pdf.jpgGenerated Thumbnailimage/jpeg16966https://bibliotecadigital.udea.edu.co/bitstreams/8e7ae930-c37c-46a0-b0ad-62b57868a7be/download26c1acc1d752450fc9fe577c0507cb67MD57falseAnonymousREAD10495/38444oai:bibliotecadigital.udea.edu.co:10495/384442025-03-26 17:59:51.915http://creativecommons.org/licenses/by-nc-nd/2.5/co/open.accesshttps://bibliotecadigital.udea.edu.coRepositorio Institucional de la Universidad de Antioquiaaplicacionbibliotecadigitalbiblioteca@udea.edu.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