[Color categorization and the structure of perceptive color].
This paper is an attempt to develop a coherent framework for understanding, simulating, and predicting color categories. The process of color categorization can be understood as a structuring of preceding color experience on the basis of statistical distribution of light in observers environment. A proposed computational model of color categorization includes: 1) distribution of R, G, B pixel values representing a sample of 630 color images of natural scenes (analogue of physical light experience); 2) transformation of the R, G, B pixel values into L*u*v* coordinates of the CIELUV color space (analogue of the process of color perception); 3) distribution of the L*u*v* coordinates representing the sample of the color images (analogue of perceived color experience); 4) k-means clustering algorithm of the L*u*v* coordinates representing the sample of the color images (analogue of the process of color categorization); 5) location and order of color clusters (analogue of location and order of color categories). The proposed computational model enables us to predict the location and order of color categories, being consistent with psycholinguistic data.
Endrikhovskiĭ
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IPO, Center for User-System Interaction, Eindhoven, The Netherlands.
D000465:Algorithms; D016000:Cluster Analysis; D003118:Color Perception / Q000145:classification* / Q000502:physiology; D006801:Humans; D008954:Models, Biological; D008960:Models, Psychological; D011578:Psycholinguistics; D012660:Semantics