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Proceedings Paper

Color road segmentation for autonomous land vehicle (ALV) road following
Author(s): Lei-Jian Liu; Yong-Ge Wu; Ke Liu; Jingyu Yang
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Paper Abstract

As the efficiency of road segmentation has a direct effect on the reliability of road following and planning -- and consequently the speed of the Autonomous Land Vehicle (ALV) -- road segmentation is one of the most preliminary and important tasks for the road following and planning of ALV, and a variety of methods for color road segmentation have been proposed. This presentation proposes a new data-fusion-based color road segmentation method in which a pyramid-based data structure and the corresponding region splitting and combination techniques for the classification of sensed areas are adopted. In the segmentation process, the roads are first segmented in two 1-D color spaces, and the data fusion technique is then used to combine the two classification results, improving the accuracy of the road segmentation.

Paper Details

Date Published: 1 February 1994
PDF: 11 pages
Proc. SPIE 2058, Mobile Robots VIII, (1 February 1994); doi: 10.1117/12.167510
Show Author Affiliations
Lei-Jian Liu, East China Institute of Technology (China)
Yong-Ge Wu, East China Institute of Technology (China)
Ke Liu, East China Institute of Technology (China)
Jingyu Yang, East China Institute of Technology (China)

Published in SPIE Proceedings Vol. 2058:
Mobile Robots VIII
William J. Wolfe; Wendell H. Chun, Editor(s)

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