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Proceedings Paper

Evaluation of color categorization for representing vehicle colors
Author(s): Nan Zeng; Jill D. Crisman
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Paper Abstract

This paper evaluates the accuracy of three color categorization techniques in describing vehicles colors for a system, AutoColor, which we are developing for Intelligent Transportation Systems. Color categorization is used to efficiently represent 24-bit color images with up to 8 bits of color information. Our inspiration for color categorization is based on the fact that humans typically use only a few color names to describe the numerous colors they perceive. Our Crayon color categorization technique uses a naming scheme for digitized colors which is roughly based on human names for colors. The fastest and most straight forward method for compacting a 24-bit representation into an 8-bit representation is to use the most significant bits (MSB) to represent the colors. In addition, we have developed an Adaptive color categorization technique which can derive a set of color categories for the current imaging conditions. In this paper, we detail the three color categorization techniques, Crayon, MSB, and Adaptive, and we evaluate their performance on representing vehicle colors in our AutoColor system.

Paper Details

Date Published: 17 February 1997
PDF: 7 pages
Proc. SPIE 2902, Transportation Sensors and Controls: Collision Avoidance, Traffic Management, and ITS, (17 February 1997); doi: 10.1117/12.267140
Show Author Affiliations
Nan Zeng, Northeastern Univ. (China)
Jill D. Crisman, Northeastern Univ. (United States)


Published in SPIE Proceedings Vol. 2902:
Transportation Sensors and Controls: Collision Avoidance, Traffic Management, and ITS
Alan C. Chachich; Marten J. de Vries, Editor(s)

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