Michael W. Schwarz
Abstract
The increasing availability of affordable color raster graphics displays has made it important to develop a better understanding of how color can be used effectively in an interactive environment. Most contemporary graphics displays offer a choice of some 16 million colors; the user's problem is to find the right color.
Folklore has it that the RGB color space arising naturally from color display hardware is user-hostile and that other color models such as the HSV scheme are preferable. Until now there has been virtually no experimental evidence addressing this point.
We describe a color matching experiment in which subjects used one of two tablet-based input techniques, interfaced through one of five color models, to interactively match target colors displayed on a CRT.
The data collected show small but significant differences between models in the ability of subjects to match the five target colors used in this experiment. Subjects using the RGB color model matched quickly but inaccurately compared with those using the other models. The largest speed difference occurred during the early convergence phase of matching. Users of the HSV color model were the slowest in this experiment, both during the convergence phase and in total time to match, but were relatively accurate. There was less variation in performance during the second refinement phase of a match than during the convergence phase.
Two-dimensional use of the tablet resulted in faster but less accurate performance than did strictly one-dimensional usage.
Significant learning occurred for users of the Opponent, YIQ, LAB, and HSV color models, and not for users of the RGB color model.
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Index Terms
- An experimental comparison of RGB, YIQ, LAB, HSV, and opponent color models
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Reviews
Paolo E. Sabella
The authors describe a color matching experiment in which subjects interactively matched target colors displayed on a CRT display. The five color models selected were RGB, YIQ, LAB, HSV, and opponent colors. Twelve groups of subjects were formed by combining two tablet-based input techniques with the five color models. While the data are presented with enough statistical detail to be credible, a casual browser can also grasp the conclusions. The surprising result is the vindication of the RGB model, which, as the authors indicate, has traditionally been regarded as user hostile. Users of the RGB model are among the fastest to make a match, although they are not the most accurate. Users of the HSV model are the slowest; however, they are more accurate. Since an independent factor is investigated, the inclusion of different input techniques complicates the results. The conclusion here is that techniques using two axes of the tablet are faster but less accurate than those that only use one axis. This study provides a basis for comparing color spaces used for interactive input. New color models can be tested by these means. For example, the opponent color model is shown to be relatively fast in achieving a match. Although the starting condition for HSV space may be questioned, the fact that a controlled experiment does exist is a great aid for graphics programmers in choosing the right form for color interaction.
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