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A Research on Detection Algorithm of Vehicle Illegal U-Turn

机译：车辆违法掉头检测算法研究

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This paper focuses on the automatic detection of illegal U-turn and recording the number of license plates. The algorithm mainly includes the position detection of vehicles' heads and tails, the marking of vehicles, the license plate recognition, and the judgment of illegal U-turn. The positions of heads and tails are detected by monitoring the headlights and the taillights in RGB color gamut. Most of the headlights are white and the taillights are largely red. In order to avoid the impact of white vehicles on results, the HOUGH Transform and face detection are utilized to determine the position of the steering wheel and the driver, which complement and verify the detection of head position. The edge of the input image needs to be enhanced to improve image quality. It will be judged whether the moving vehicle has had an illegal U-turn. The effectiveness of the algorithm is verified by simulation with MATLAB. Through the analysis of experimental results, it is demonstrated that the algorithm designed in this paper is feasible and achieves the desired design requirements.
机译：本文着重于对非法掉头的自动检测并记录车牌的数量。该算法主要包括车辆头部和尾部的位置检测，车辆标记，车牌识别以及非法掉头的判断。通过监视RGB色域中的前灯和尾灯，可以检测出头和尾的位置。大多数前灯是白色的，而尾灯在很大程度上是红色的。为了避免白色车辆对结果产生影响，HOUGH变换和面部检测用于确定方向盘和驾驶员的位置，从而补充并验证对头部位置的检测。需要增强输入图像的边缘以改善图像质量。将判断行驶中的车辆是否有非法掉头。通过MATLAB仿真验证了该算法的有效性。通过对实验结果的分析表明，本文设计的算法是可行的，达到了预期的设计要求。

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