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A real time vehicle counting based on adaptive tracking approach for highway videos

机译:基于自适应跟踪的高速公路视频实时车辆计数

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Detection, Tracking, and Counting the number of vehicles is the main foundation of intelligent systems for monitoring vehicle traffic flow. This research is going to perform vehicle detection using background subtraction algorithm and morphology operation. The result of those methods categorized as candidate object. Contour detection applied to define the object from its candidate. Vehicle is determined using threshold area of contour properties. The detected vehicles is tracked using an adaptive distance similarity measurement. Then, vehicle will be counted using the counting line after its vehicles pass that line. The proposed method is tested in four datasets with different challenges such as differences in light, weather, camera vibration, and image blurring. The research obtains satisfactory results especially in noon and rainy dataset with the accuracy higher than 93% for vehicle detection, tracking, and counting. The proposed method is able to detect, perform tracking, and counting the number of vehicles in a real time for highway videos.
机译:检测,跟踪和计算车辆数量是用于监视车辆交通流量的智能系统的主要基础。这项研究将使用背景减除算法和形态学运算来执行车辆检测。这些方法的结果归类为候选对象。轮廓检测应用于根据其候选对象定义对象。使用轮廓属性的阈值区域确定车辆。使用自适应距离相似性测量来跟踪检测到的车辆。然后,在车辆经过该线之后,将使用计数线对该车辆进行计数。所提出的方法在具有不同挑战(例如光线,天气,相机振动和图像模糊)的四个数据集中进行了测试。该研究尤其在正午和多雨的数据集上获得了令人满意的结果,其在车辆检测,跟踪和计数方面的准确性均高于93%。所提出的方法能够针对高速公路视频实时检测,执行跟踪和计数车辆数量。

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