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Vision-Based Overload Detection System for Land Transportation

机译:基于视觉的土地运输过载检测系统

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Overloaded trucks pose a threat to highway traffic, increasing the rate and severity of accidents, while damaging road infrastructure. Enabling an efficient overload detection method at existing weighing stations would facilitate regulatory compliance. This paper presents a real-time, accurate truck overload detection system that leverages existing surveillance cameras installed at weighing stations. To achieve this goal, we applied computer vision algorithms on video from an indoor camera monitoring a digital display and on another outdoor camera monitoring the station's weighing bridge. The truck's actual weight is obtained by reading the numeric digit display on images from the indoor camera, while the truck's maximum load capacity is estimated by recognizing the its wheel layout using the video from the outdoor camera. Through evaluation using video data from a weighing station, the optical digit recognition algorithm achieves an accuracy of 99.0%, while the load capacity estimation algorithm achieves an accuracy of 93.18%.
机译:超载卡车对公路交通构成威胁,提高事故的速度和严重程度,同时损坏道路基础设施。在现有称重站实现有效的过载检测方法将促进法规遵从性。本文介绍了一个实时准确的卡车过载检测系统,可利用安装在称重站的现有监控摄像头。为实现这一目标,我们从室内摄像机监控数字显示器和监控站称重桥的另一户外摄像头上的视频上应用了计算机视觉算法。通过读取来自室内摄像头的图像上的数字数字显示器来获得卡车的实际重量,而通过使用来自户外摄像机的视频识别其轮子布局,估计卡车的最大负载能力。通过使用来自称重站的视频数据的评估,光学数字识别算法实现了99.0%的精度,而负载能力估计算法达到93.18%的精度。

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