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dc.contributor.authorSilva, Jesússpa
dc.contributor.authorRondon, Carlosspa
dc.contributor.authorCabrera, Danelysspa
dc.contributor.authorPineda, Omarspa
dc.date.accessioned2021-02-04T23:28:57Z
dc.date.available2021-02-04T23:28:57Z
dc.date.issued2020
dc.identifier.urihttps://hdl.handle.net/11323/7830spa
dc.description.abstractColor is a human perception of the light reflected by an object. It is an appreciation that depends on the way the human´s eyes detect the reflected light and the way the brain processes it. However, for industry, it is an attribute of product appearance and its observation allows the detection of certain anomalies and defects [1]. Therefore, color is a characteristic that allows to judge an object by creating conditions for its acceptance or rejection [2]. In this research, a laboratory experiment was carried out to analyze different factors involved in visual color evaluations in textiles. A complete factorial experiment design was carried out in which the analyzed factors were lighting, noise, color and participants.spa
dc.format.mimetypeapplication/pdfspa
dc.language.isoeng
dc.publisherCorporación Universidad de la Costaspa
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 Internationalspa
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/spa
dc.sourceIOP Conference Series: Materials Science and Engineeringspa
dc.subjectVisual assessmentspa
dc.subjectColor discriminationspa
dc.subjectTextile colorspa
dc.subjectVisual ergonomicsspa
dc.titleInfluence of lighting and noise on visual color assessment in textilesspa
dc.typeArtículo de revistaspa
dc.source.urlhttps://www.researchgate.net/publication/342502262_Influence_of_lighting_and_noise_on_visual_color_assessment_in_textilesspa
dc.rights.accessrightsinfo:eu-repo/semantics/openAccessspa
dc.identifier.doi10.1088/1757-899X/872/1/012033spa
dc.identifier.instnameCorporación Universidad de la Costaspa
dc.identifier.reponameREDICUC - Repositorio CUCspa
dc.identifier.repourlhttps://repositorio.cuc.edu.co/spa
dc.relation.references[1] David, A., Esposito, T., Houser, K., Royer, M., Smet, K. A., & Whitehead, L. (2020). A vector field color rendition model for characterizing color shifts and metameric mismatch. Leukos, 16(2), 99-114.spa
dc.relation.references[2] Henao-Rodríguez, C., Lis-Gutiérrez, J. P., Gaitán-Angulo, M., Malagón, L. E., & Viloria, A. (2018, May). Econometric analysis of the industrial growth determinants in Colombia. In Australasian Database Conference (pp. 316-321). Springer, Cham.spa
dc.relation.references[3] Dentoni, V., Grosso, B., Massacci, G., & Soddu, G. P. (2020). Visual impact evaluation of mines and quarries: the updated Lvi method. Environmental Earth Sciences, 79(5), 1-11.spa
dc.relation.references[4] Li, X., Powell, N. B., & Michielsen, S. (2020). Print clarity on digitally printed textiles–a quantitative evaluation. The Journal of The Textile Institute, 111(1), 108-121.spa
dc.relation.references[5] Khanh, T. Q., Bodrogi, P., Guo, X., & Anh, P. Q. (2019). Towards a user preference model for interior lighting Part 1: Concept of the user preference model and experimental method. Lighting Research & Technology, 51(7), 1014-1029.spa
dc.relation.references[6] Li, X., Powell, N. B., & Michielsen, S. (2020). Print clarity on digitally printed textiles–a quantitative evaluation. The Journal of The Textile Institute, 111(1), 108-121.spa
dc.relation.references[7] Gerken, M., Schlemmer, H., & Becker, T. (2019, May). Color discrimination of a short wave colorimeter. In Infrared Technology and Applications XLV (Vol. 11002, p. 1100210). International Society for Optics and Photonics.spa
dc.relation.references[8] Hagtvedt, H. (2019). Dark is durable, light is user‐friendly: The impact of color lightness on two product attribute judgments. Psychology & Marketing.spa
dc.relation.references[9] Zhou, Z., Wang, C., Zhang, J., & Zhu, Z. (2020). Color difference classification of solid color printing and dyeing products based on optimization of the extreme learning machine of the improved whale optimization algorithm. Textile Research Journal, 90(2), 135-155.spa
dc.relation.references[10] Zhang, J., Wen, X., & Whang, M. (2020). Recognition of Emotion According to the Physical Elements of the Video. Sensors, 20(3), 649.spa
dc.relation.references[11] Catalina, T., Ene, A., & Biro, A. (2019). Visual and acoustic performance of shading devices–real scale laboratory measurements. In E3S Web of Conferences (Vol. 111). EDP Sciences.spa
dc.relation.references[12] Barati, B., Karana, E., Sekulovski, D., & Pont, S. C. (2017). Retail lighting and textiles: Designing a lighting probe set. Lighting Research & Technology, 49(2), 173-194.spa
dc.relation.references[13] Lavoué, G., Langer, M., Peytavie, A., & Poulin, P. (2018). A Psychophysical Evaluation of Texture Compression Masking Effects. IEEE transactions on visualization and computer graphics, 25(2), 1336-1346.spa
dc.relation.references[14] Ying, G., Xinyan, Z., Xiang, L., & Ye, Z. (2018). Quantitative characterization appreciation of golden citrine golden by the irradiation of [FeO4] 4−. Arabian journal of chemistry, 11(6), 918-923.spa
dc.relation.references[15] Zhou, Y., & Tang, R. C. (2017). Influence of fixing treatment on the color fastness and bioactivities of silk fabric dyed with curcumin. The Journal of the Textile Institute, 108(6), 1050-1056.spa
dc.relation.references[16] Parody, A., Viloria, A., Lis, J. P., Malagón, L. E., Calí, E. G., & Palma, H. H. (2018, June). Application of an experimental design of D-optimum mixing based on restrictions for the optimization of the pre-painted steel line of a steel producer and marketing company. In International Conference on Data Mining and Big Data (pp. 729-738). Springer, Chamspa
dc.type.coarhttp://purl.org/coar/resource_type/c_6501spa
dc.type.contentTextspa
dc.type.driverinfo:eu-repo/semantics/articlespa
dc.type.redcolhttp://purl.org/redcol/resource_type/ARTspa
dc.type.versioninfo:eu-repo/semantics/acceptedVersionspa
dc.type.coarversionhttp://purl.org/coar/version/c_ab4af688f83e57aaspa
dc.rights.coarhttp://purl.org/coar/access_right/c_abf2spa


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