RIT‐DuPont supra‐threshold color‐tolerance individual color‐difference pair dataset

Abstract

The RIT-DuPont dataset has been used extensively for formula development and testing since its inception during the 1980's, for example, in the development of CIE94 and CIEDE2000. The dataset was published as 156 color-tolerances, T 50 , along specific vector directions about 19 color centers. Probit analysis was used to transform judgments of 958 color-difference pairs by 50 observers to these 156 tolerances. For most statistical significance testing, the number of samples determines the confidence limits. Thus, there was an interest in publishing the individual color-difference pair visual and colorimetric data to improve the precision of significance testing. From these 958 pairs, 828 pairs had determinable visual differences. The others had either excessive visual uncertainty or had unanimous visual judgments such that visual differences were undefined. In addition, a method was devised to assign visual uncertainty to each of these pairs using the principles of maximum likelihood and the T 50 values. Comparisons were made between the T 50 and individual color-difference pair data both including and omitting uncertainty weightings. The weighted dataset was found to be equivalent to the T 50 tolerances.

Revisiting the weighting function for lightness in the CIEDE2000 colour‐difference formula

“…However, colour-difference formulas developed before CIEDE2000 proposed different S L functions. Following a CIE request [27], after the development of CIEDE2000 a number of new experimental visual datasets on colour differences have been compiled [28][29][30][31][32][33][34][35]. These proposals are related to divergent results found in different experiments [23][24][25].…”

Method to determine the degrees of consistency in experimental datasets of perceptual color differences

“…Specifically, step 2 gives a degree of consistency for each color pair, which is highly useful information for any dataset. It should be noted that, with a few exceptions [2,25], the reliability of individual color pairs is not provided in available color-difference datasets, where only average ΔE and ΔV values are provided. The reliability of ΔV may be the standard deviation of the answers reported by the observers or something similar.…”

“…When this information is not available, at least our method is able to provide information on the reliability of an individual color pair, based on its agreement or consistency with neighboring color pairs (assuming that there are a reasonable minimum number of such neighbor color pairs). This information on the specific reliability of each color pair can also be considered to compute a weighted STRESS [8,14,24,25] for any color-difference formula, which may be a good option for a better assessment of the merit of such a formula. For example, using CIEDE2000 as the color-difference formula, and the weights provided by the consistency index CS i described in step 2, we find that the weighted STRESS value (WSTRESS) for the COM-corrected dataset was 26.14 while the STRESS value was 27.53.…”

“…The use of a weighted STRESS [25,14] also proved useful to assess the degree of consistency assigned to each color pair using the new method proposed in the current paper. However, bearing in mind that the STRESS index is not very sensitive to the removal of a small number of color pairs from a dataset, in addition to STRESS we have also used the mean square error (MSE) to analyze our current results.…”

Measuring color differences in gonioapparent materials used in the automotive industry

“…w i =1 ; i=1,…, 56), the WSTRESS index assigns different weights to each color pair, those with higher accuracy (lower inter-observer variability) having a higher weight. Following Berns [23], here we have adopted as weight a reciprocal variance, defined as the square of the average visual difference of all observers divided by 4 times their standard deviation (both measured in CIELAB units), as shown in Eq. (3) …”