Cálculo de la incertidumbre de la Temperatura de Color Correlacionada (CCT) mediante un método de Monte Carlo

Ilustraciones y fotografías

Autores:: Chávez Cañón, Miguel Ángel

Tipo de recurso:

Fecha de publicación:: 2021

Institución:: Universidad Nacional de Colombia

Repositorio:: Universidad Nacional de Colombia

Idioma:: spa

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dc.title.spa.fl_str_mv	Cálculo de la incertidumbre de la Temperatura de Color Correlacionada (CCT) mediante un método de Monte Carlo
dc.title.translated.eng.fl_str_mv	Calculation of the Correlated Color Temperature (CCT) uncertainty using a Monte Carlo method
title	Cálculo de la incertidumbre de la Temperatura de Color Correlacionada (CCT) mediante un método de Monte Carlo
spellingShingle	Cálculo de la incertidumbre de la Temperatura de Color Correlacionada (CCT) mediante un método de Monte Carlo 620 - Ingeniería y operaciones afines Método Montecarlo Monte Carlo method Fotometría Photometry Luz Light Correlated Color Temperature (CCT) Uncertainty Colorimetry Temperatura de color Incertidumbre Colorimetría
title_short	Cálculo de la incertidumbre de la Temperatura de Color Correlacionada (CCT) mediante un método de Monte Carlo
title_full	Cálculo de la incertidumbre de la Temperatura de Color Correlacionada (CCT) mediante un método de Monte Carlo
title_fullStr	Cálculo de la incertidumbre de la Temperatura de Color Correlacionada (CCT) mediante un método de Monte Carlo
title_full_unstemmed	Cálculo de la incertidumbre de la Temperatura de Color Correlacionada (CCT) mediante un método de Monte Carlo
title_sort	Cálculo de la incertidumbre de la Temperatura de Color Correlacionada (CCT) mediante un método de Monte Carlo
dc.creator.fl_str_mv	Chávez Cañón, Miguel Ángel
dc.contributor.advisor.none.fl_str_mv	Jesús M., Quintero Q.
dc.contributor.author.none.fl_str_mv	Chávez Cañón, Miguel Ángel
dc.subject.ddc.spa.fl_str_mv	620 - Ingeniería y operaciones afines
topic	620 - Ingeniería y operaciones afines Método Montecarlo Monte Carlo method Fotometría Photometry Luz Light Correlated Color Temperature (CCT) Uncertainty Colorimetry Temperatura de color Incertidumbre Colorimetría
dc.subject.lemb.none.fl_str_mv	Método Montecarlo Monte Carlo method Fotometría Photometry Luz Light
dc.subject.proposal.eng.fl_str_mv	Correlated Color Temperature (CCT) Uncertainty Colorimetry
dc.subject.proposal.spa.fl_str_mv	Temperatura de color Incertidumbre Colorimetría
description	Ilustraciones y fotografías
publishDate	2021
dc.date.accessioned.none.fl_str_mv	2021-09-01T19:09:59Z
dc.date.available.none.fl_str_mv	2021-09-01T19:09:59Z
dc.date.issued.none.fl_str_mv	2021
dc.type.spa.fl_str_mv	Trabajo de grado - Maestría
dc.type.driver.spa.fl_str_mv	info:eu-repo/semantics/masterThesis
dc.type.version.spa.fl_str_mv	info:eu-repo/semantics/acceptedVersion
dc.type.content.spa.fl_str_mv	Text
dc.type.redcol.spa.fl_str_mv	http://purl.org/redcol/resource_type/TM
status_str	acceptedVersion
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dc.identifier.instname.spa.fl_str_mv	Universidad Nacional de Colombia
dc.identifier.reponame.spa.fl_str_mv	Repositorio Institucional Universidad Nacional de Colombia
dc.identifier.repourl.spa.fl_str_mv	https://repositorio.unal.edu.co/
url	https://repositorio.unal.edu.co/handle/unal/80072 https://repositorio.unal.edu.co/
identifier_str_mv	Universidad Nacional de Colombia Repositorio Institucional Universidad Nacional de Colombia
dc.language.iso.spa.fl_str_mv	spa
language	spa
dc.relation.references.spa.fl_str_mv	Y. Ohno and W. Davis, “NIST CQS version 9.0 (Hoja de cálculo en Excel).” NIST, E.E.U.U NIST, p., 2011. W. Davis and Y. Ohno, “Color quality scale,” Opt. Eng., vol. 49, no. 3, p. 033602, 2010, doi: 10.1117/1.3360335. Y. Ohno, “Spectral design considerations for white LED color rendering,” Opt. Eng., vol. 44, no. 11, 2005, doi: 10.1117/1.2130694. A. Ugale, T. N. Kalyani, and S. J. Dhoble, “Potential of europium and samarium β-diketonates as red light emitters in organic light-emitting diodes,” in Lanthanide-Based Multifunctional Materials: From OLEDs to SIMs, 2018. Y. Ohno and W. Davis, “Rationale of Color Quality Scale,” Energy, 2010. D. Judd, “A flattery index for artificial illumiants,” IES Trans., 1967. W. A. Thornton, “A validation of the color-preference index,” J. Illum. Eng. Soc., vol. 4, no. 1, 1974, doi: 10.1080/00994480.1974.10732288. M. S. Rea and J. P. Freyssinier-Nova, “Color rendering: A tale of two metrics,” Color Res. Appl., vol. 33, no. 3, 2008, doi: 10.1002/col.20399. K. Hashimoto, T. Yano, M. Shimizu, and Y. Nayatani, “New method for specifying color-rendering properties of light sources based on feeling of contrast,” Color Res. Appl., vol. 32, no. 5, 2007, doi: 10.1002/col.20338. P. Bodrogi, S. Brückner, and T. Q. Khanh, “Ordinal scale based description of colour rendering,” Color Res. Appl., vol. 36, no. 4, 2011, doi: 10.1002/col.20629. K. A. G. Smet, W. R. Ryckaert, M. R. Pointer, G. Deconinck, and P. Hanselaer, “A memory colour quality metric for white light sources,” Energy Build., vol. 49, 2012, doi: 10.1016/j.enbuild.2012.02.008. A. Ẑukauskas, R. Vaicekauskas, F. Ivanauskas, H. Vaitkeviĉius, P. Vitta, and M. S. Shur, “Statistical approach to color quality of solid-state lamps,” IEEE J. Sel. Top. Quantum Electron., vol. 15, no. 6, 2009, doi: 10.1109/JSTQE.2009.2034587. F. Szabó, P. Bodrogi, and J. Schanda, “A colour harmony rendering index based on predictions of colour harmony impression,” Light. Res. Technol., vol. 41, no. 2, 2009, doi: 10.1177/1477153509103067. K. A. G. Smet, J. Schanda, L. Whitehead, and R. M. Luo, “CRI2012: A proposal for updating the CIE colour rendering index,” Light. Res. Technol., vol. 45, no. 6, 2013, doi: 10.1177/1477153513481375. Illuminating Engineering Society of North America, “IES Method for Evaluating Light Source Color Renditon,” New York, 2015. A. David et al., “Development of the IES method for evaluating the color rendition of light sources,” Opt. Express, vol. 23, no. 12, 2015, doi: 10.1364/oe.23.015888. Illuminating Engineering Society of North, IES Method for Evaluating Light Source Color Renditon. New York, 2018. Illuminating Engineering Society of North, “IES Method for Evaluating Light Source Color Rendition,” New York, 2020. doi: ISBN# 978-0-87995-379-9. I. Ashdown et al., “Correspondence: In support of the IES method of evaluating light source colour rendition,” Lighting Research and Technology, vol. 47, no. 8. 2015, doi: 10.1177/1477153515617392. R. Windisch, G. Heidel, U. Binder, and K. Bergenek, “Impact of spectral features of common LED lighting systems on TM-30 color indices,” Opt. Express, vol. 25, no. 3, 2017, doi: 10.1364/oe.25.001824. M. Royer, “Analysis of color rendition specification criteria,” 2019, doi: 10.1117/12.2507283. 2021 Westinghouse Electric Corporation, “Color Rendering Index,” 2021. https://www.westinghouselighting.com/lighting-education/color-rendering-index-cri.aspx. M. Garrett and R. Stech, “Energy Policy Act of 1992,” in Encyclopedia of Transportation: Social Science and Policy, 2014. CIE, “CIE 13.3-1995, Method of measuring and Specifying Colour Rendering Properties of Light Sources,” Cie 13.3, 1995. D. B. Judd, “Standard Response Functions for Protanopic and Deuteranopic Vision,” J. Opt. Soc. Am., vol. 39, no. 6, 1949, doi: 10.1364/josa.39.000505. F. Zhang, “Evaluation of changing the components involved in CIE color rendering index,” Optik (Stuttg)., vol. 219, 2020, doi: 10.1016/j.ijleo.2020.165261. X. Guo and K. W. Houser, “A review of colour rendering indices and their application to commercial light sources,” Light. Res. Technol., vol. 36, no. 3, 2004, doi: 10.1191/1365782804li112oa. K. Smet, W. R. Ryckaert, M. R. Pointer, G. Deconinck, and P. Hanselaer, “Correlation between color quality metric predictions and visual appreciation of light sources,” Opt. Express, vol. 19, no. 9, 2011, doi: 10.1364/oe.19.008151. P. Raynham, “ Book review: The Lighting Handbook 10 th Edition, Reference and Application ,” Light. Res. Technol., vol. 44, no. 4, 2012, doi: 10.1177/1477153512461896. K. W. Houser, M. Wei, A. David, M. R. Krames, and X. S. Shen, “Review of measures for light-source color rendition and considerations for a two-measure system for characterizing color rendition,” Opt. Express, vol. 21, no. 8, 2013, doi: 10.1364/oe.21.010393. K. Hashimoto and Y. Nayatani, “Visual clarity and feeling of contrast,” Color Res. Appl., vol. 19, no. 3, 1994, doi: 10.1002/col.5080190305. Illuminating Engineering Society of North, “IES Method for Evaluating Light Source Color Rendetion,” Illuminating Engineering Society, New York, p. 37, 2015. Illuminating Engineering Society, “IES-TM-30-18: Method for Evaluating Light Source Color Rendition,” New York, 2018. doi: 978-0-87995-379-9. “CIE 224:2017 CIE 2017 COLOUR FIDELITY INDEX FOR ACCURATE SCIENTIFIC USE Vienna: CIE Central Bureau, 2017 52 pp, and is readily available from the http://www.techstreet.com/cie/ or from the National Committees of the CIE. €219.00; Members €72.99,” Color Research and Application, 2017. K. A. G. Smet, A. David, and L. Whitehead, “Why Color Space Uniformity and Sample Set Spectral Uniformity Are Essential for Color Rendering Measures,” LEUKOS - J. Illum. Eng. Soc. North Am., vol. 12, no. 1–2, 2016, doi: 10.1080/15502724.2015.1091356. M. P. Royer and M. Wei, “The Role of Presented Objects in Deriving Color Preference Criteria from Psychophysical Studies,” LEUKOS - J. Illum. Eng. Soc. North Am., vol. 13, no. 3, 2017, doi: 10.1080/15502724.2016.1271339. C. Li, M. R. Luo, M. R. Pointer, and P. Green, “Comparison of real colour gamuts using a new reflectance database,” Color Res. Appl., vol. 39, no. 5, 2014, doi: 10.1002/col.21827. J. Tajima, M. Tsukada, H. Haneishi, and N. Ojima, “‘Representative Data Selection and their Evaluation for Standard Object Colour Spectra Database (SOCS),’” J. Inst. Image Electron. Eng. Japan, vol. 31, no. 5, 2002, doi: 10.11371/iieej.31.768. S. E. J. Armold, S. Faruq, V. Savolainen, P. W. McOwan, and L. Chittka, “FReD: The floral reflectance database - a web portal for analyses of flower colour,” PLoS One, vol. 5, no. 12, 2010, doi: 10.1371/journal.pone.0014287. S. Jost, C. Cauwerts, and P. Avouac, “CIE 2017 color fidelity index Rf: a better index to predict perceived color difference?,” J. Opt. Soc. Am. A, vol. 35, no. 4, 2018, doi: 10.1364/josaa.35.00b202. D. Durmus and W. Davis, “EVALUATION OF HUE SHIFT FORMULAE IN CIELAB AND CAM02,” 2019, doi: 10.25039/x46.2019.po005. R. M. Lou, G. Cui, and C. Li, “Uniform colour spaces based on CIECAM02 colour apperance model,” Color Res. Appl., vol. 31, no. 4, 2006, doi: 10.1002/col.20227. M. Roger and K. HOuser, “Understanding and Applying TM-30-15,” U.S. Department of Energy, IES, 2015. https://www.energy.gov/sites/prod/files/2015/09/f26/tm30-intro-webinar_9-15-15.pdf. https://www.techstreet.com/, “IES TM-30-20,” IES Method for Evaluating Light Source Color Rendition, 2020. https://www.techstreet.com/standards/ies-tm-30-20?utm_campaign=tracker&utm_medium=email&utm_source=internal&utm_term=IES TM-30-20&product_id=2207652. E. Desimoni and B. Brunetti, “Uncertainty of measurement: Approaches and open problems,” Ann. Chim., vol. 95, no. 5, 2005, doi: 10.1002/adic.200590032. Y. Ohno, “CIE Fundamentals for Color Measurements,” 2000. CIE, “CIE 198:2011, Determination of measurement uncertainties in photometry,” 2011.
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dc.publisher.spa.fl_str_mv	Universidad Nacional de Colombia
dc.publisher.program.spa.fl_str_mv	Bogotá - Ingeniería - Maestría en Ingeniería - Ingeniería Eléctrica
dc.publisher.department.spa.fl_str_mv	Departamento de Ingeniería Eléctrica y Electrónica
dc.publisher.faculty.spa.fl_str_mv	Facultad de Ingeniería
dc.publisher.place.spa.fl_str_mv	Bogotá, Colombia
dc.publisher.branch.spa.fl_str_mv	Universidad Nacional de Colombia - Sede Bogotá
institution	Universidad Nacional de Colombia
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spelling	Atribución-NoComercial-SinDerivadas 4.0 Internacionalhttp://creativecommons.org/licenses/by-nc-nd/4.0/info:eu-repo/semantics/openAccesshttp://purl.org/coar/access_right/c_abf2Jesús M., Quintero Q.caa3b413f9365f41f84ca2df0aeba4beChávez Cañón, Miguel Ángel78a533d2b418055d6bbd0ec191b8a1d22021-09-01T19:09:59Z2021-09-01T19:09:59Z2021https://repositorio.unal.edu.co/handle/unal/80072Universidad Nacional de ColombiaRepositorio Institucional Universidad Nacional de Colombiahttps://repositorio.unal.edu.co/Ilustraciones y fotografíasSe presentan e implementan los métodos actuales más utilizados y aceptados tanto para el cálculo de la Temperatura de Color Correlacionada (CCT) como para su respectiva incertidumbre. Los métodos actuales se basan en el enfoque clásico de incertidumbre de acuerdo con la "Guía para la expresión de la incertidumbre de la medición" (GUM, JCGM 100:2008) cuyo fundamento matemático se basa en aproximaciones de series de Taylor. Para resolver los problemas actuales debidos a aproximaciones, supuestos, restricciones y complejidad en el cálculo de incertidumbre de este parámetro se propone la implementación de un Método de Monte Carlo (MCM) de acuerdo con los suplementos GUM S1 (JCGM 101:2008) y GUM S2 (JCGM 102:2012). Este trabajo presenta la implementación del método propuesto y los métodos más importantes utilizados actualmente, con su respectiva comparación. Para esto se utilizan espectros de fuentes de luz típicos ya definidos bien conocidos y usados en la literatura. Además, se desarrolla un software que permite realizar las estimaciones de incertidumbre el cual tendría como objetivo ser usado por el laboratorio de ensayos eléctricos de la Universidad Nacional de Colombia, con esto se espera mejorar la exactitud y confiabilidad del servicio que actualmente presta este laboratorio en cuanto a la incertidumbre de CCT. (Texto tomado de la fuente).The most widely used and accepted current methods are presented and implemented both for the calculation of the Correlated Color Temperature (CCT) and their respective uncertainty. Current methods are based on the classical uncertainty approach according to the GUM (Guide to the expression of uncertainty in measurement, JCGM 100: 2008) whose mathematical foundation is based on Taylor series approximations. To solve current problems due to approximations, assumptions, restrictions, and complexity in calculating the uncertainty of this parameter, the implementation of a Monte Carlo method, MCM, is proposed, according to the supplements GUM S1 (JCGM 101: 2008) and GUM S2 (JCGM 102: 2012). This work presents the implementation of a proposed method and the most important methods currently used, with their respective comparison. For this, spectra of typical and well-known light sources commonly used in the literature will be used. In addition, a software is developed allowing the Electrical Testing Laboratory (LABE) of the Universidad Nacional de Colombia to make uncertainty estimates which, it is expected to improve its accuracy and reliability of the CCT measurements service that is currently provided.MaestríaMagíster en Ingeniería EléctricaIluminación y Eficiencia Energéticaxxii, 163 páginasapplication/pdfspaUniversidad Nacional de ColombiaBogotá - Ingeniería - Maestría en Ingeniería - Ingeniería EléctricaDepartamento de Ingeniería Eléctrica y ElectrónicaFacultad de IngenieríaBogotá, ColombiaUniversidad Nacional de Colombia - Sede Bogotá620 - Ingeniería y operaciones afinesMétodo MontecarloMonte Carlo methodFotometríaPhotometryLuzLightCorrelated Color Temperature (CCT)UncertaintyColorimetryTemperatura de colorIncertidumbreColorimetríaCálculo de la incertidumbre de la Temperatura de Color Correlacionada (CCT) mediante un método de Monte CarloCalculation of the Correlated Color Temperature (CCT) uncertainty using a Monte Carlo methodTrabajo de grado - Maestríainfo:eu-repo/semantics/masterThesisinfo:eu-repo/semantics/acceptedVersionTexthttp://purl.org/redcol/resource_type/TMY. Ohno and W. Davis, “NIST CQS version 9.0 (Hoja de cálculo en Excel).” NIST, E.E.U.U NIST, p., 2011. W. Davis and Y. Ohno, “Color quality scale,” Opt. Eng., vol. 49, no. 3, p. 033602, 2010, doi: 10.1117/1.3360335. Y. Ohno, “Spectral design considerations for white LED color rendering,” Opt. Eng., vol. 44, no. 11, 2005, doi: 10.1117/1.2130694. A. Ugale, T. N. Kalyani, and S. J. Dhoble, “Potential of europium and samarium β-diketonates as red light emitters in organic light-emitting diodes,” in Lanthanide-Based Multifunctional Materials: From OLEDs to SIMs, 2018. Y. Ohno and W. Davis, “Rationale of Color Quality Scale,” Energy, 2010. D. Judd, “A flattery index for artificial illumiants,” IES Trans., 1967. W. A. Thornton, “A validation of the color-preference index,” J. Illum. Eng. Soc., vol. 4, no. 1, 1974, doi: 10.1080/00994480.1974.10732288. M. S. Rea and J. P. Freyssinier-Nova, “Color rendering: A tale of two metrics,” Color Res. Appl., vol. 33, no. 3, 2008, doi: 10.1002/col.20399. K. Hashimoto, T. Yano, M. Shimizu, and Y. Nayatani, “New method for specifying color-rendering properties of light sources based on feeling of contrast,” Color Res. Appl., vol. 32, no. 5, 2007, doi: 10.1002/col.20338. P. Bodrogi, S. Brückner, and T. Q. Khanh, “Ordinal scale based description of colour rendering,” Color Res. Appl., vol. 36, no. 4, 2011, doi: 10.1002/col.20629. K. A. G. Smet, W. R. Ryckaert, M. R. Pointer, G. Deconinck, and P. Hanselaer, “A memory colour quality metric for white light sources,” Energy Build., vol. 49, 2012, doi: 10.1016/j.enbuild.2012.02.008. A. Ẑukauskas, R. Vaicekauskas, F. Ivanauskas, H. Vaitkeviĉius, P. Vitta, and M. S. Shur, “Statistical approach to color quality of solid-state lamps,” IEEE J. Sel. Top. Quantum Electron., vol. 15, no. 6, 2009, doi: 10.1109/JSTQE.2009.2034587. F. Szabó, P. Bodrogi, and J. Schanda, “A colour harmony rendering index based on predictions of colour harmony impression,” Light. Res. Technol., vol. 41, no. 2, 2009, doi: 10.1177/1477153509103067. K. A. G. Smet, J. Schanda, L. Whitehead, and R. M. Luo, “CRI2012: A proposal for updating the CIE colour rendering index,” Light. Res. Technol., vol. 45, no. 6, 2013, doi: 10.1177/1477153513481375. Illuminating Engineering Society of North America, “IES Method for Evaluating Light Source Color Renditon,” New York, 2015. A. David et al., “Development of the IES method for evaluating the color rendition of light sources,” Opt. Express, vol. 23, no. 12, 2015, doi: 10.1364/oe.23.015888. Illuminating Engineering Society of North, IES Method for Evaluating Light Source Color Renditon. New York, 2018. Illuminating Engineering Society of North, “IES Method for Evaluating Light Source Color Rendition,” New York, 2020. doi: ISBN# 978-0-87995-379-9. I. Ashdown et al., “Correspondence: In support of the IES method of evaluating light source colour rendition,” Lighting Research and Technology, vol. 47, no. 8. 2015, doi: 10.1177/1477153515617392. R. Windisch, G. Heidel, U. Binder, and K. Bergenek, “Impact of spectral features of common LED lighting systems on TM-30 color indices,” Opt. Express, vol. 25, no. 3, 2017, doi: 10.1364/oe.25.001824. M. Royer, “Analysis of color rendition specification criteria,” 2019, doi: 10.1117/12.2507283. 2021 Westinghouse Electric Corporation, “Color Rendering Index,” 2021. https://www.westinghouselighting.com/lighting-education/color-rendering-index-cri.aspx. M. Garrett and R. Stech, “Energy Policy Act of 1992,” in Encyclopedia of Transportation: Social Science and Policy, 2014. CIE, “CIE 13.3-1995, Method of measuring and Specifying Colour Rendering Properties of Light Sources,” Cie 13.3, 1995. D. B. Judd, “Standard Response Functions for Protanopic and Deuteranopic Vision,” J. Opt. Soc. Am., vol. 39, no. 6, 1949, doi: 10.1364/josa.39.000505. F. Zhang, “Evaluation of changing the components involved in CIE color rendering index,” Optik (Stuttg)., vol. 219, 2020, doi: 10.1016/j.ijleo.2020.165261. X. Guo and K. W. Houser, “A review of colour rendering indices and their application to commercial light sources,” Light. Res. Technol., vol. 36, no. 3, 2004, doi: 10.1191/1365782804li112oa. K. Smet, W. R. Ryckaert, M. R. Pointer, G. Deconinck, and P. Hanselaer, “Correlation between color quality metric predictions and visual appreciation of light sources,” Opt. Express, vol. 19, no. 9, 2011, doi: 10.1364/oe.19.008151. P. Raynham, “ Book review: The Lighting Handbook 10 th Edition, Reference and Application ,” Light. Res. Technol., vol. 44, no. 4, 2012, doi: 10.1177/1477153512461896. K. W. Houser, M. Wei, A. David, M. R. Krames, and X. S. Shen, “Review of measures for light-source color rendition and considerations for a two-measure system for characterizing color rendition,” Opt. Express, vol. 21, no. 8, 2013, doi: 10.1364/oe.21.010393. K. Hashimoto and Y. Nayatani, “Visual clarity and feeling of contrast,” Color Res. Appl., vol. 19, no. 3, 1994, doi: 10.1002/col.5080190305. Illuminating Engineering Society of North, “IES Method for Evaluating Light Source Color Rendetion,” Illuminating Engineering Society, New York, p. 37, 2015. Illuminating Engineering Society, “IES-TM-30-18: Method for Evaluating Light Source Color Rendition,” New York, 2018. doi: 978-0-87995-379-9. “CIE 224:2017 CIE 2017 COLOUR FIDELITY INDEX FOR ACCURATE SCIENTIFIC USE Vienna: CIE Central Bureau, 2017 52 pp, and is readily available from the http://www.techstreet.com/cie/ or from the National Committees of the CIE. €219.00; Members €72.99,” Color Research and Application, 2017. K. A. G. Smet, A. David, and L. Whitehead, “Why Color Space Uniformity and Sample Set Spectral Uniformity Are Essential for Color Rendering Measures,” LEUKOS - J. Illum. Eng. Soc. North Am., vol. 12, no. 1–2, 2016, doi: 10.1080/15502724.2015.1091356. M. P. Royer and M. Wei, “The Role of Presented Objects in Deriving Color Preference Criteria from Psychophysical Studies,” LEUKOS - J. Illum. Eng. Soc. North Am., vol. 13, no. 3, 2017, doi: 10.1080/15502724.2016.1271339. C. Li, M. R. Luo, M. R. Pointer, and P. Green, “Comparison of real colour gamuts using a new reflectance database,” Color Res. Appl., vol. 39, no. 5, 2014, doi: 10.1002/col.21827. J. Tajima, M. Tsukada, H. Haneishi, and N. Ojima, “‘Representative Data Selection and their Evaluation for Standard Object Colour Spectra Database (SOCS),’” J. Inst. Image Electron. Eng. Japan, vol. 31, no. 5, 2002, doi: 10.11371/iieej.31.768. S. E. J. Armold, S. Faruq, V. Savolainen, P. W. McOwan, and L. 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Cálculo de la incertidumbre de la Temperatura de Color Correlacionada (CCT) mediante un método de Monte Carlo

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