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Proceedings Paper

Computing color categories
Author(s): Sergej N. Endrikhovski
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Paper Abstract

This paper is an attempt to develop a coherent framework for understanding, modeling, and computing color categories. The main assumption is that the structure of color category systems originates from the statistical structure of the perceived color environment. This environment can be modeled as color statistics of natural images in some perceptual and approximately uniform color space (e.g., the CIELUV color space). The process of color categorization can be modeled as the grouping of the color statistics by clustering algorithms (e.g., K-means). The proposed computational model enable to predict the location, order, and number of color categories. The model is examined on the basis of K-means clustering analysis of statistics of 630 natural images in the CIELUV color space. In general, the predictions are consistent with Berlin and Kay, and Boynton and Oslon data.

Paper Details

Date Published: 2 June 2000
PDF: 9 pages
Proc. SPIE 3959, Human Vision and Electronic Imaging V, (2 June 2000); doi: 10.1117/12.387172
Show Author Affiliations
Sergej N. Endrikhovski, IPO Ctr. for Research on User-System Interaction/Eindhoven Univ. of Technology (United States)

Published in SPIE Proceedings Vol. 3959:
Human Vision and Electronic Imaging V
Bernice E. Rogowitz; Thrasyvoulos N. Pappas, Editor(s)

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