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Proceedings Paper

New color road segmentation method
Author(s): Ke Liu; Yanxing Liu; Jingyu Yang; Yong-Qing Cheng; Nian-Chun Gu
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Paper Abstract

Road segmentation is the critical step in a vision system for outdoor road following. This paper presents a new method for color road segmentation. The basic idea of the method is as follows: each pixel of a color image consists of red, green, and blue intensity values; it can be considered as a feature vector in 3-D RGB space, and the road segmentation can be translated into a statistic classification problem. First, a color normalization transform is used to erase the shadows in a color image; then, the optimal discriminant plane technique is used for feature decorrelation; finally, road segmentation is completed by a minimum distance classifier designed on the optimal discriminant plane. We have done a lot of experiments, and the results show that the present method is effective.

Paper Details

Date Published: 14 February 1992
PDF: 7 pages
Proc. SPIE 1613, Mobile Robots VI, (14 February 1992); doi: 10.1117/12.135189
Show Author Affiliations
Ke Liu, East China Institute of Technology (China)
Yanxing Liu, East China Institute of Technology (China)
Jingyu Yang, East China Institute of Technology (China)
Yong-Qing Cheng, East China Institute of Technology (China)
Nian-Chun Gu, East China Institute of Technology (China)

Published in SPIE Proceedings Vol. 1613:
Mobile Robots VI
William J. Wolfe; Wendell H. Chun, Editor(s)

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