• Resumo

    Algoritmo Haar Cascade Aplicado na Detecção das Placas de Parada Obrigatória e de Velocidade Máxima Permitida

    Data de publicação: 04/09/2020

    ABSTRACT
    Systems able to assist drivers in the safe driving of vehicles
    provide several advantages, such as the reduction of traffic
    accidents, mostly with fatalities, normally caused by human
    failures, whether for distractions or even problems related to
    lighting or climate change. Based on this, this research aims to
    present a computational model capable of detect stop signs and
    speed limit signs, so that it contributes to the development of
    progressively intelligent vehicles. The system was implemented
    in Phyton programming language, with the support of OpenCV
    library, and it was divided into two steps: firstly it was
    performed the training and classification of the objects through
    Haar Cascade classification method, and in the second step, in
    order to improve the results, colors relevant to the object were
    identified using the HSV color space. During the experiments,
    the proposed algorithm presented satisfactory results, with a hit
    rate of 91% for speed limit signs and 93% for stop signs. In order
    to refine the proposed solution, it is intended for the next steps
    to include traffic sign information recognition, to either describe
    the specified speed on the detected objects and further reduce
    false positives.

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