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.
Color road segmentation for autonomous land vehicle (ALV) road following
Mobile Robots VIII ; 1993 ; Boston,MA,United States
Proc. SPIE ; 2058
1994-02-01
Conference paper
Electronic Resource
English
Color Image Segmentation for Autonomous Land Vehicle Road Following
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