A Perceptual Colour Segmentation Algorithm Christopher G. Healey and James T. Enns
This paper presents a simple method for segmenting colour regions into categories like red, green, blue, and yellow. We are interested in studying how colour categories influence colour selection during scientific visualization. The ability to name individual colours is also important in other problem domains like real-time displays, user-interface design, and medical imaging systems. Our algorithm uses the Munsell and CIE LUV colour models to automatically segment a colour space like RGB or CIE XYZ into ten colour categories. Users are then asked to name a small number of representative colours from each category. This provides three important results: a measure of the perceptual overlap between neighbouring categories, a measure of a category's strength, and a user-chosen name for each strong category.
We evaluated our technique by segmenting known colour regions from the RGB, HSV, and CIE LUV colour models. The names we obtained were accurate, and the boundaries between different colour categories were well defined. We concluded our investigation by conducting an experiment to obtain user-chosen names and perceptual overlap for ten colour categories along the circumference of a colour wheel in CIE LUV.
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