How Well Can People Predict Subtractive Mixing?

This study is concerned with the design of effective colour tools to allow users to quickly and accurately select a given colour in a digital-display environment. It has been shown that the choice of colour space (for example, RGB colour space compared with a more perceptually relevant space) influences performance (speed and accuracy) in certain colour-related tasks. We suggest that the nature of the colour-mixing model may also be a factor in certain tasks such as the selection of a target colour from a colour-selector tool. It is our hypothesis that users have a more accurate internal model for how subtractive colour mixing works than for additive colour mixing. The purpose of this work is to determine whether it is indeed the case that observers possess better internal models for subtractive colour mixing than for additive colour mixing. In Experiment 1 the variance in observers' abilities to predict the result of subtractive colour mixing is compared using real physical samples and using a computer monitor (CRT). Although the variance obtained on the CRT was greater than that obtained using the physical samples, the difference was not statistically significant. In Experiment 2, the abilities of observers to predict subtractive and additive mixing were directly compared using samples displayed on a CRT. Observers' abilities to predict additive mixtures were not as good as their abilities to predict subtractive mixtures (p < 0.05).