Traditional vehicle target recognition technology mainly uses artificial or artificial intelligence methods for recognition in the visible light band. Aiming at the problems of low level of intelligence and low efficiency of vehicle recognition at night and low visibility, an improved SVM recognition algorithm based on infrared images is proposed. In this research, the infrared images of small vehicles, medium vehicles and large vehicles at night are used as the object, and the infrared characteristic information of vehicles is extracted based on the histogram of directional gradient (HOG), and the internal parameters are optimized by improving the support vector machine. After the algorithm is trained, the accurate recognition rate of all vehicles can reach 98%, and the effect of the improved algorithm is significantly better than that of the unimproved algorithm, which provides a certain reference for the application of machine learning in vehicle target recognition.


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    Title :

    Research on vehicle target recognition based on infrared image processing


    Contributors:
    Liao, Junbo (author) / Yuan, Hongxue (author) / Li, Yanbiao (author) / Geng, Shunshan (author)

    Conference:

    International Conference on Optics and Machine Vision (ICOMV 2022) ; 2022 ; Guangzhou,China


    Published in:

    Proc. SPIE ; 12173


    Publication date :

    2022-05-12





    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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