How colourful language can improve your image

Color gamutColourful language usually refers euphemistically to the kind of expletives and oaths you hear in a barrack room brawl. But, in the context of technology it could be the next big thing in colour printing.

Colour and natural language experts at Xerox have been working on what sounds like an entirely new way to get the best out of your digital photos. Their research could allow you to talk to your printer and tell it to “make the green a ‘mossy’ green” or “make the sky more sky blue”. More technically, you might one day be able to do all the kinds of colour and contrast corrections that are usually the preserve of programs like Photoshop, with simple phrases sent to the printer itself.

The approach speed up the workflow for graphic artists, printers, photographers and other image professionals and their assistants who could save time side-stepping the on-screen fine tuning process of printouts.

“You shouldn’t have to be a colour expert to make the sky a deeper blue or add a bit of yellow to a sunset,” research leader Geoff Wolfe says. The software is still in the development stages, but works by translating human descriptions of colour – “emerald green”, “brick red”, “sky-blue pink” – into the precise numerical codes printers use to control the amount of each primary colour they deposit at a single point in the printed image.

“Today, especially in the office environment, there are many non-experts who know how they would like colour to appear but have no idea how to manipulate the color to get what they want,” Woolfe adds. Moreover, the vast majority of computer screens in “non-expert” offices are setup incorrectly for screen to print comparisons and so cause the whole gamut of problems when a document that looks okay on screen is printed. Simple commands to rectify such issues avoid the problem of having to know how to set up the screen and ambient lighting.

Woolfe’s discovery could mean that colour adjustments can be made on devices like office printers and commercial presses without having to deal with the mathematics. For instance, cardinal red on a printer or monitor is really expressed by a set of mathematical coordinates that identify a specific region in a three-dimensional space, which is the gamut of all the colours that the device can display or print. To make that colour less orange, the colour expert distorts (morphs) that region to a new region in the gamut.

The ability to use common words to do this gamut morphing and adjust colour would have far-reaching implications for non-experts as well as graphic artists, printers, photographers and other professionals who spend a significant amount of time fine tuning the colours in documents.

“In the end it’s all about usability,” Woolfe adds, “Colour is so prevalent today, you shouldn’t have to be an expert to handle it.”

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5 thoughts on “How colourful language can improve your image

  1. Hi,
    I found this post because I got thinking the same thing, especially after reading J. Cage’s Color and Culture and the more recent publications of Geoff Woolfe and Nathan Moroney.
    Finally I decided to do something about it and I am running an On-line Colour Naming Experiment in English, Spanish and Greek as part of my MSc major on colour naming and colour categorisation within different cultures.
    The experiment takes only about 10 minutes to complete and the participants will also have the chance to win a fine art print by the artist Valero Doval. The research is being conducted by the Colour Imaging Group at the London College of Communication, part of the University of the Arts London.

  2. Response to Ed’s comment:

    Hi Ed. It was interesting to read your comments on the natural language technology I’ve been working on for the past year or so. You raise a really interesting point that really got me thinking. Unfortunately, after thinking it through, it seems to me that we cannot use this technology to gain insight into how different people perceive colors. The reason for this is that color perception lies entirely with an individual’s consciousness. Color naming, however, is a learned response. We learn, generally in our early childhood, to associate a certain name with the perception that results from observing a particular colored object. So, while virtually everybody learns to associate the name ‘blue’ with the color of the sky on a clear, sunny day, we cannot be certain that the internal perception of that color is identical for each person.
    We know that the physiological make-up of the human visual system can vary markedly from one individual to another. It is fair to assume that this results in the signals being sent from the visual system to the brain to differ between individuals. Still there is remarkable agreement in the color naming behavior across a range of individuals. This is simply because we have all learned to associate the color name ‘blue’ with the color perception that results from looking at the sky.

    Response to David’s comment:
    Hi David. The issues you raise are certainly important considerations. In fact similar questions were asked by several of the scientists at the Inter-Society Color Council conference where I recently presented my results. As it turns out, the examples you give regarding arguments over color names do not affect this technology significantly. There are many synonyms for a single color stimulus and the technology is able to map multiple names to the same region in color space. A good example of this is ‘bluish-green’. This color might be called ‘cyan’ by some people and ‘turquoise’ or ‘aqua’ by others. The technology will map all these names to a similar region of color space. Another point to keep in mind is that color naming is not intended to be a precise and specific specification of color, so color names map to a fuzzy region in color space, not to an exact, specific point. There are certain color applications where this fuzziness is actually an advantage rather than a disadvantage. Color adjustment of images is one such example. By using fuzzy descriptors like color names we obtain results that are smooth and pleasing. Highly precise color specifications in such applications can lead to undesirable artifacts such as contours.

  3. Ed, interesting thought. Yes, there are lots of even common terms for different colours, such as turquoise, khaki, mauve, and crimson, that people argue about over and over, at least they do in this house when it comes to clothes and such like. But, seriously, this new Xerox technology probably has even more scope for producing inaccurate colours than a simple lack of technical savvy among printing users. I’ve emailed Woolfe at Xerox and asked for his thoughts on this.

  4. Hello,

    This post got me thinking about whether this tech could be used to study difference in how people perceive colours.

    Since colour exists in the brain, one person’s idea of what ‘brick red’ looks like may be very different to another’s. ‘Brick red’ is most likely to apply to a wide range of combinations of light wavelengths, and it would be interesting to see how these ranges vary between individuals, throughout development, between ethnic groups etc.

    After all, who hasn’t become embroiled in an argument about whether something is ‘actually’ blue or green, and so on?

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