Visual impairment/color-blindness (VICB) can be challenging in many situations especially while crossing a pedestrian/cross-walk or driving a vehicle. A Traffic Light Recognition System (TLRs) may help in the accurate detection of traffic lights using a hand-held mobile device. TLR helps in reduction of accidental mortality rates. It will also help improving transportation and mobility for old aged and differently-abled people. TLR system detects the presence of traffic light in the environment and incorporates guiding assistance by notifying its color and shape to a VICB person. There may be enormous challenges in correct detection of Traffic Lights, involving non-working lights, illuminations, ego-vehicles, weather, trees, and other obstructions. A detailed discussion of the TLR System is provided for data acquisition, pre-processing, localization,feature extraction and verification stages. Finally, the conclusions are drawn and possible future scope of the field is discussed.


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    Titel :

    A Survey of Machine Learning Techniques Applied for Automatic Traffic Light Recognition


    Weitere Titelangaben:

    Lect. Notes in Networks, Syst.


    Beteiligte:
    Chen, Joy Iong-Zong (Herausgeber:in) / Tavares, João Manuel R. S. (Herausgeber:in) / Iliyasu, Abdullah M. (Herausgeber:in) / Du, Ke-Lin (Herausgeber:in) / Sarita (Autor:in) / Kumar, Anuj (Autor:in)

    Kongress:

    International Conference on Image Processing and Capsule Networks ; 2021 ; Bangkok, Thailand May 27, 2021 - May 28, 2021



    Erscheinungsdatum :

    10.09.2021


    Format / Umfang :

    14 pages





    Medientyp :

    Aufsatz/Kapitel (Buch)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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