In order to realize lane mark identifying and tracking on such conditions as uneven road surface materials and different illumination etc, this paper proposes a new method which combines an image segmentation technique based on maximum entropy with a bi-normalized adjustable template. First, applying image window variation technology, this method first realizes the better road image segmentation based on maximize one-dimension entropy. Second, lane mark parameters can be acquired based on the bi-normalized adjustable template. Finally lane mark real-time tracking is realized by applying trapezia AOI method.


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    Title :

    Lane mark segmentation method based on maximum entropy


    Contributors:
    Yu Tianhong, (author) / Wang Rongben, (author) / Jin Lisheng, (author) / Chu Jiangwei, (author) / Guo Lie, (author)


    Publication date :

    2005-01-01


    Size :

    396516 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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