Performance testing of color‐difference metrics using a color tolerance dataset

Abstract

A color‐difference dataset was developed for testing the performance of color metrics. The dataset comprises 45 color‐difference vectors varying in five directions at nine color centers under conditions typical of commercial color decisions. Probit analysis was used to estimate the parameters of the population distribution of tolerances for each vector. In addition to estimating the median tolerance, the anlysis allows one to estimate the uncertainty of a tolerance and to test the adequacy of the underlying model tolerance distribution. The median tolerances were used to specify 45 color‐difference pairs with equal visual color‐difference magnitudes. The performance of eight color‐difference metrics was compared using the normalized standard deviation of the color differences of the visually equal difference pairs as a measure of uniformity. A bootstrap statistical technique was used to quantify the variation in performance with varying samples of color centers and color‐difference directions and to determine the significance of observed differences in uniformity performance. Some metrics based on weighted CIELAB dl*, dC*, dH* color‐difference components had significantly superior performance compared to the CIE recommended color‐difference metrics.

A preliminary comparison of CIE color differences to textile color acceptability using average observers

“…3,4,15,18 -20 This can affect the results of color experiments. 18 Since these experiments are difficult and time consuming, the observers who were tested are often connected with the lab and may have previous experience, whereas the end users of textile products are ordinary consumers who generally do not have a high degree of experience in color discrimination. With more experienced observers, smaller color discrimination thresholds than normal are obtained.…”

Suprathreshold color-difference ellipsoids for surface colors

“…The experiments were carried out under typiIn a previous study 1,2 a color-tolerance data set was develcal illuminating and viewing conditions, closely following oped, seeking to improve the relationship between visual those adopted by the CIE in recent recommendations. 3,4 and numerical color-difference evaluation for industrial Probit analysis was used to convert the visual decisions to colorimetry.…”

Erratum

“…Color difference literature shows that the square of the correlation coefficients relating measured data to perceptual data is only about 70%, 19 although recent studies 20 report higher correlation from the use of a gray anchor-pair. Although in our experiments the visual tasks are more complex than the perception of a color difference, we have checked the potential improvement achieved in Experiment I using an anchor-pair.…”