
Proceedings Paper
Color space analysis of road detection algorithmsFormat | Member Price | Non-Member Price |
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Paper Abstract
Color space analysis of classification-based segmentation algorithms provides insights into the capabilities of the color vision system. In standard pattern recognition theory, classification algorithms are categorized by their discriminant functions in feature space. This analysis is applied to color classification methods used in road detection systems. There have been many systems that use classification techniques. By examining these road detection system in color space, a relationship can be seen between their color model representation and their capabilities and limitations.
Paper Details
Date Published: 1 October 1991
PDF: 15 pages
Proc. SPIE 1569, Stochastic and Neural Methods in Signal Processing, Image Processing, and Computer Vision, (1 October 1991); doi: 10.1117/12.48404
Published in SPIE Proceedings Vol. 1569:
Stochastic and Neural Methods in Signal Processing, Image Processing, and Computer Vision
Su-Shing Chen, Editor(s)
PDF: 15 pages
Proc. SPIE 1569, Stochastic and Neural Methods in Signal Processing, Image Processing, and Computer Vision, (1 October 1991); doi: 10.1117/12.48404
Show Author Affiliations
Jill D. Crisman, Northeastern Univ. (United States)
Published in SPIE Proceedings Vol. 1569:
Stochastic and Neural Methods in Signal Processing, Image Processing, and Computer Vision
Su-Shing Chen, Editor(s)
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