Measuring color differences in gonioapparent materials used in the automotive industry
Metadatos
Afficher la notice complèteAuteur
Melgosa Latorre, Manuel; Gómez Robledo, Luis; Cui, G.; Li, C.; Perales, E.; Martínez-Verdú, F. M.; Dauser, T.Editorial
Institute of Physics (IOP)
Materia
Measure Color Gonioapparent material Quality Artificial color-vision applications
Date
2015Referencia bibliográfica
Melgosa Latorre, M.; et al. Measuring color differences in gonioapparent materials used in the automotive industry. Journal of Physics: conference series, 605: 012006 (2015). [http://hdl.handle.net/10481/36637]
Patrocinador
This research was supported by the Ministry of Economy and Competitiveness of Spain, research projects FIS2013-40661-P and DPI2011-30090-C02, with European Research Development Fund (ERDF), as well as by the National Science Foundation of China (grant number 61178053).Résumé
This paper illustrates how to design a visual experiment to measure color differences in gonioapparent materials and how to assess the merits of different advanced color-difference formulas trying to predict the results of such experiment. Successful color-difference formulas are necessary for industrial quality control and artificial color-vision applications. A color- difference formula must be accurate under a wide variety of experimental conditions including the use of challenging materials like, for example, gonioapparent samples. Improving the experimental design in a previous paper [Melgosaet al., Optics Express 22, 3458-3467 (2014)], we have tested 11 advanced color-difference formulas from visual assessments performed by a panel of 11 observers with normal colorvision using a set of 56 nearly achromatic colorpairs of automotive gonioapparent samples. Best predictions of our experimental results were found for the AUDI2000 color-difference formula, followed by color-difference formulas based on the color appearance model CIECAM02. Parameters in the original weighting function for lightness in the AUDI2000 formula were optimized obtaining small improvements. However, a power function from results provided by the AUDI2000 formula considerably improved results, producing values close to the inter-observer variability in our visual experiment. Additional research is required to obtain a modified AUDI2000 color-difference formula significantly better than the current one.