Traffic light recognition is a key technology for intelligent vehicles and Advanced Driver Assistance Systems (ADAS). This paper proposes a multi-feature fusion based real-time traffic light recognition algorithm for intelligent vehicles. In the region of interest determined by the vanishing line, technologies including color segmentation, blob detection, and structural feature extraction are employed individually to obtain a set of candidate locations. A fusion algorithm is developed to integrate these results and compute a score for all these possible locations of traffic lights. The score of each candidate denotes its probability of being a traffic light. The final detection is achieved by fusing its score with temporal and geographic information. Extensive experimental results on a real intelligent vehicle show that the proposed algorithm is effective and efficient.


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    Titel :

    A multi-feature fusion based traffic light recognition algorithm for intelligent vehicles


    Beteiligte:
    Zhang, Yue (Autor:in) / Xue, Jianru (Autor:in) / Zhang, Geng (Autor:in) / Zhang, Yingwei (Autor:in) / Zheng, Nanning (Autor:in)


    Erscheinungsdatum :

    01.07.2014


    Format / Umfang :

    555896 byte





    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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