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.


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    Titel :

    Color road segmentation for autonomous land vehicle (ALV) road following


    Beteiligte:
    Liu, Lei-Jian (Autor:in) / Wu, Yong-Ge (Autor:in) / Liu, Ke (Autor:in) / Yang, Jingyu (Autor:in)

    Kongress:

    Mobile Robots VIII ; 1993 ; Boston,MA,United States


    Erschienen in:

    Erscheinungsdatum :

    01.02.1994





    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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