Speed Detection using Haar-Cascade Classifier and Pixel per Meter

Palak Vadhadiya, Nitin Jayavarapu, Lasya Mudigonda, Sai Sravani Parnem
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Abstract

Modern highways cannot exist unless traffic safety is prioritized. As a result, while determining speed restrictions for a certain route, the condition of the road and its tendency for accidents are considered. Speed monitoring cameras are strategically positioned along the route to detect motorists who exceed the speed limit. The traditional speed radar gun has been replaced with speed monitoring cameras. The main purpose of this research work is to create a speed-detecting camera by using image processing to process the videos using Haar Cascade in Python.
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使用haar级联分类器和像素每米的速度检测
除非优先考虑交通安全,否则现代高速公路不可能存在。因此,在确定某条路线的限速时,要考虑道路状况及其发生事故的可能性。沿路战略性地设置了速度监控摄像头,以检测超速驾驶的司机。传统的测速雷达炮已被测速监控摄像机所取代。本研究工作的主要目的是通过使用Python中的Haar Cascade使用图像处理来处理视频,从而创建一个速度检测相机。
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