Saturday, January 28, 2012

Harmonious colors: from alchemy to science

Last weekend three storms swept through the Bay Area and it was a good thing, because it cleaned up the very dirty air. The attendees of Electronic Imaging enjoyed a perfect weather.

At the session on the Dark Side of Color, I gave a presentation on my thoughts about the discussion in the color language workgroup meeting at the last AIC conference, which was held in Zurich. I would like to thank Dr. Michael H. Brill for asking a particularly good and relevant question.

Unfortunately SlideShare had some problems parsing the uploaded PDF file. The original PDF can be downloaded from here.

The paper is available with Open Access through this link:

The citation is: Giordano B. Beretta and Nathan M. Moroney, "Harmonious colors: from alchemy to science", Proc. SPIE 8292, 82920I (2012); doi:10.1117/12.915839

Finally, here is the abstract:

There is a very long tradition in designing color palettes for various applications. Although color palettes have been influenced by the available colorants, starting with the advent of aniline dyes there have been few physical limits on the choice of individual colors. This abundance of choices exacerbates the problem of limiting the number of colors in a palette.

The traditional solution is that of "color forecasting." Color consultants assess the sentiment or affective state of a target customer class and compare it with new colorants offered by the industry. They assemble a limited color palette, name the colors according to the sentiment, and publish their result.

The color forecasting business is very labor intensive and difficult, thus for years computer engineers have tried to come up with algorithms to design harmonious color palettes, alas with little commercial success. Contrary to the auditory sense, there is no known physiological mechanism sustaining harmony and the term "harmonious" just has the informal meaning of "going well together."

We argue that the intellectual flaw resides in the belief that a masterful individual can devise a "perfect methodology" that the engineer can then reduce to practice in a computer program. We suggest that the correct approach is to consider color forecasting as an act of distillation, where a palette is digested from the sentiment of a very large number of people. We describe how this approach can be reduced to an algorithm by replacing the subjective process with a data analytic process.

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