Automatic Color Palette Creation from Words

We present an automatic framework to extract color palettes from words. This is a novel approach in comparison to existing solutions, e.g. manual creation or extraction from images. The associations between words and colors are deduced from a large database of 6 million tagged images using a scalable data-mining technique. The palette creation can be constrained by the user to achieve a desired hue template. We first focus on single words and then extend to entire texts. We compare our results against Adobe Kuler, a widely used online platform of manually created color palettes. We show that our approach performs slightly better than its non-automatic counterpart in terms of user’s preference rankings. This is a good result because our method is fully automatic whereas Kuler relies on users’ palettes that are manually created and annotated.

Published in:
Proceedings of the IS&T 21st Color and Imaging Conference, 69-74
Presented at:
IS&T 21st Color and Imaging Conference, Albuquerque, New Mexico, November 4-8, 2013
Focal Paper

Note: The status of this file is: Anyone

 Record created 2013-10-24, last modified 2020-10-25

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