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首页> 外文期刊>Indonesian Journal of Electronics and Instrumentation Systems >Sistem Pengukur Kecepatan Kendaraan Berbasis Pengolahan Video
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Sistem Pengukur Kecepatan Kendaraan Berbasis Pengolahan Video

机译:基于视频处理的车速测量系统

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This system is implemented by digital image processing to detect the objects and measure the speed. This system using background subtraction method with Gaussian Mixture Model (GMM) algorithm. Background subtraction will separate background and detected objects. Coordinates of the objects midpoint used as the the object moving value in pixel. The actual distance also measured in meters where the distance is limited by region of interest (ROI). The ROI is 160 pixel. Having obtained the moving objects time from previous frame to current frame so the value of pixel/s can converted to km/h. System testing the measurement validation, calculate the speed after being validated, and the influence of light intensity. The speed validation process uses average speed of early three frames speed as the reference for the speed measurement in the next frame. The average speed accuracy of 3 frames early gives a percentage error about 1,92% - 15,75%. When validation is performed on the entire reading frame of video, it produces an error range 1,21% - 21,37%. The system works well in the morning, afternoon, and evening conditions with light intensity about 600-1900 lux. While at night with 0-5 lux light intensity range, the system can’t work properly.
机译:该系统通过数字图像处理实现,以检测物体并测量速度。该系统采用背景减法和高斯混合模型(GMM)算法。背景减法将背景和检测到的对象分开。对象中点的坐标,以像素为单位的对象移动值。实际距离也以米为单位,其中距离受关注区域(ROI)的限制。 ROI为160像素。获得了移动物体从前一帧到当前帧的时间,因此像素/ s的值可以转换为km / h。系统对测量验证进行测试,验证后计算速度,以及光强度的影响。速度验证过程将早期三帧速度的平均速度用作下一帧速度测量的参考。早期3帧的平均速度准确度给出了大约1,92%-15,75%的百分比误差。当对视频的整个阅读帧执行验证时,它产生的误差范围为1,21%-21,37%。该系统在早晨,下午和傍晚的光线强度约为600-1900 lux的情况下都能正常工作。夜间在0-5 lux的光照强度范围内,系统无法正常运行。

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