In this paper, a road segmentation method was proposed. It consists of four major steps: background image generation, foreground object extraction, background pasting, and road localization. To begin, the background image of a scene is generated. The generated background image is then used to fast extract foreground objects from each input video image. The background patches corresponding to the extracted foreground objects are pasted on an image, called the road image. A major component of the road region will gradually be constructed by repeating the previous steps. To obtain the full road region, two more tasks are performed, they are hole filling and road localization. Hole filling is accomplished by invoking a morphological process, and road localization is achieved using a fuzzy-shadowed set theoretic technique. It is this technique that the preceding steps are greatly simplified. Road segmentation is of use for a number of traffic applications, such as traffic surveillance, traffic flow measurement, traffic accident/incident detection, vehicle guidance, and driver assistance. Road segmentation provide useful information for precluding from further consideration irrelevant objects, events and activities so as to prevent their interferences and unnecessary computations. The experimental results have revealed that the proposed method can effectively detect the road area without a priori information about both camera setup and image scale.


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    Title :

    Road segmentation with fuzzy and shadowed sets


    Additional title:

    Straßensegmentierung mit schattierten Fuzzy-Mengen


    Contributors:


    Publication date :

    2004


    Size :

    6 Seiten, 5 Bilder, 14 Quellen


    Type of media :

    Conference paper


    Type of material :

    Print


    Language :

    English