Color alphabet

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Example of a RGB Color Mapping System developed by Christian Faur
Example of a RGB Color Mapping System developed by Christian Faur

Color alphabet is a one to one mapping of a subset of discrete colors to a standardized set of signs (alphabet or graphemes) that allows one to construct meaning out of color directly and unambiguously using an existing system of writing.

The choice of colors should be distinct to insure that the translation of textual elements remains readable.

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[edit] Examples of writing systems that use color

There have been systems put in place in the past that use colors to signify abstract meaning. These systems range from those used in flags and military uniforms used to identify nations [see Political Color] to the color and patterned Setts of Scottish kilts used to identify clans or groups.

The Incas are believed to have used colored strings and knots as a system of writing, known as Quipu, to recording data. This was probably one of the first uses of mapping color directly to language.

In modern times there are many color coding systems used to display information, these range from electronic color code for identifying the values or ratings of electronic components to utility color code used for identifying existing underground utilities. Kromofons is an alphabet in which each of the 26 letters of English is represented by a unique color.

[edit] The encoding system

Although choice of colors used map to the individual graphemes of an alphabetical system is somewhat arbitrary, it should take into account the limitations of human color vision and perception. A good starting point is to use the colors that are the most easily identifiable based on perceptual research so they can be decoded with a high degree of accuracy by people that do not experience color blindness.

Work done in a 1969 study[1] by Berlin and Kay has show that there are similarities in color naming across different languages. The set of 11 color names shown to be most common in the study are (red, green, yellow, blue, black, white, pink, gray, orange, brown, purple) with the addition of cyan or azure in some languages that have 12 basic color terms.

Colin Ware[2] sites several categories that should be used for nominal information coding when it comes to color. Colors used should be distinct or possess a high degree of separation on a uniform color space. One should avoid using similar hues within a single system and take the background color into account as this has the tendency to change the appearance of foreground colors. One should use differences in saturation as well as luminance as these adjustments are more easily perceived then differences in hue alone, and insure that the color-coded objects are not too small.

Letter frequency should be then next criteria used to map the chosen colors to text. The letters with the greatest frequency (in English these would be the letters e, t, a, o, i, n and s) should be mapped to the most distinct colors as they will occur most often in words and need to be quickly interpreted

Colored Font example: 1. The "quick" brown fox jumped-over the lazy dog.
Colored Font example: 1. The "quick" brown fox jumped-over the lazy dog.

Finally, the color needs to be displayed or rendered in some fashion. This can take on the form of painting directly on paper to a fully developed typeface that imparts a stylistic unity to the colored writing. A typeface used to display colored text should use glyphs that have as large of a surface area as possible for a given space. Recent research[3] done on reading and decoding shows that the shape of a cluster of letters, which was thought to be an essential component for recognize words when reading, has turn out not to be important factor. This makes the use of identically shaped glyphs within a readable color typeface possible.

[edit] See also

[edit] References

  1. ^ Brent Berlin, Paul Kay. Basic Color Terms: Their Universality and Evolution. Berkeley: University of California Press (1991)
  2. ^ Ware, Colin. Information Visualization: Perception for Design. San Francisco, CA: Morgan Kaufmann (2000)
  3. ^ Larson, Kevin. ”The Science of Word Recognition or how I learned to stop worrying and love the bouma” Advanced Reading Technology, Microsoft Corporation (2004)

[edit] External links