The traffic sign detection and recognition is an integral part of Advanced Driver Assistance System (ADAS). Traffic signs provide information about the traffic rules, road conditions and route directions and assist the drivers for better and safe driving. Traffic sign detection and recognition system has two main stages: The first stage involves the traffic sign localization and the second stage classifies the detected traffic signs into a particular class. This article provides the challenges involved in the real-time detection of traffic signs. A review of the existing detection methods such as color based, shape based and learning based detection is presented. It also discusses about the feature matching and machine learning algorithms used in the traffic sign recognition stage.


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    Title :

    Automatic traffic sign detection and recognition: A review


    Contributors:
    Swathi, M (author) / Suresh, K. V. (author)


    Publication date :

    2017-02-01


    Size :

    312059 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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