Traffic safety states can be divided into safe and dangerous according to the attributes of video images of traffic safety states. We propose a synergic neural network recognition model based on prototype pattern by analyzing various methods on intelligent video processing. Our proposed method realizes real time classification of traffic safety states with high accuracy of traffic safety states recognition. The experimental results validate that the accuracy of classification of proposed method arrives at 87.5%, increased by 16.2% compared to traditional neural network methods.


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    Title :

    An Intelligent Recognition Algorithm on Traffic Safety States



    Published in:

    Applied Mechanics and Materials ; 433-435 ; 1388-1391


    Publication date :

    2013-10-15


    Size :

    4 pages




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English




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