With the increasing number of vehicles, vehicle detection has become an important part of intelligent transportation system. At present, most detection algorithms are only suitable for normal light conditions, but the detection performance is poor for low illumination conditions. In order to achieve effective vehicle detection under low illumination conditions, this paper proposes an image enhancement algorithm to increase the contrast of the image, thereby greatly improving the effect of vehicle detection. First, the image contrast is enhanced through an adaptive contrast stretching algorithm. Secondly, the bilateral filtering algorithm is used to filter out the noise in the image. Finally, the detection system based on Haar features and AdaBoost classifier is used to detect vehicles. Experimental results show that the proposed algorithm can effectively enhance image contrast, highlight vehicle information, and the vehicle detection accuracy rate under low illumination conditions reaches 87.04%.


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    Title :

    Low-illumination environment vehicle detection based on optimized adaptive image enhancement


    Contributors:
    Zhao, Kun (author) / Liu, Jian (author) / Xiao, Xiaocheng (author)

    Conference:

    2021 International Conference on Image, Video Processing, and Artificial Intelligence ; 2021 ; Shanghai,China


    Published in:

    Proc. SPIE ; 12076


    Publication date :

    2021-11-11





    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English




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