Paper
18 November 2013 Testing the AUDI2000 colour-difference formula for solid colours using some visual datasets with usefulness to automotive industry
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Proceedings Volume 8785, 8th Iberoamerican Optics Meeting and 11th Latin American Meeting on Optics, Lasers, and Applications; 87858P (2013) https://doi.org/10.1117/12.2026601
Event: 8th Ibero American Optics Meeting/11th Latin American Meeting on Optics, Lasers, and Applications, 2013, Porto, Portugal
Abstract
Colour-difference formulas are tools employed in colour industries for objective pass/fail decisions of manufactured products. These objective decisions are based on instrumental colour measurements which must reliably predict the subjective colour-difference evaluations performed by observers’ panels. In a previous paper we have tested the performance of different colour-difference formulas using the datasets employed at the development of the last CIErecommended colour-difference formula CIEDE2000, and we found that the AUDI2000 colour-difference formula for solid (homogeneous) colours performed reasonably well, despite the colour pairs in these datasets were not similar to those typically employed in the automotive industry (CIE Publication x038:2013, 465-469). Here we have tested again AUDI2000 together with 11 advanced colour-difference formulas (CIELUV, CIELAB, CMC, BFD, CIE94, CIEDE2000, CAM02-UCS, CAM02-SCD, DIN99d, DIN99b, OSA-GP-Euclidean) for three visual datasets we may consider particularly useful to the automotive industry because of different reasons: 1) 828 metallic colour pairs used to develop the highly reliable RIT-DuPont dataset (Color Res. Appl. 35, 274-283, 2010); 2) printed samples conforming 893 colour pairs with threshold colour differences (J. Opt. Soc. Am. A 29, 883-891, 2012); 3) 150 colour pairs in a tolerance dataset proposed by AUDI. To measure the relative merits of the different tested colour-difference formulas, we employed the STRESS index (J. Opt. Soc. Am. A 24, 1823-1829, 2007), assuming a 95% confidence level. For datasets 1) and 2), AUDI2000 was in the group of the best colour-difference formulas with no significant differences with respect to CIE94, CIEDE2000, CAM02-UCS, DIN99b and DIN99d formulas. For dataset 3) AUDI2000 provided the best results, being statistically significantly better than all other tested colour-difference formulas.
© (2013) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Juan Martínez-García, Manuel Melgosa, Luis Gómez-Robledo, Changjun Li, Min Huang, Haoxue Liu, Guihua Cui, M. Ronnier Luo, and Thomas Dauser "Testing the AUDI2000 colour-difference formula for solid colours using some visual datasets with usefulness to automotive industry", Proc. SPIE 8785, 8th Iberoamerican Optics Meeting and 11th Latin American Meeting on Optics, Lasers, and Applications, 87858P (18 November 2013); https://doi.org/10.1117/12.2026601
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Cited by 2 scholarly publications.
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KEYWORDS
Visualization

Tolerancing

Solids

Americium

Statistical analysis

System on a chip

Visual optics

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