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A
Perceptual
Colour
Segmentation
Algorithm
Christopher
G.
Healey and
James
T.
Enns
TR-96-09
ABSTRACT
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.