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Traffic flow detection method based on fusion of frames differencing and background differencing

机译:基于帧差分和背景差分融合的交通流检测方法

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摘要

Study optimization of traffic flow accuracy detection problem. For moving targets' speed and external environment are the main factors of influencing traffic flow detection. It is easy to cause undetection and misjudgment of traffic flow detection. In order to overcome traditional frame differencing method and background differencing's inadequation when using singlely, an intelligent traffic detection method based on fusion of the frame differencing method and background differencing method is proposed by existing algorithm in this passage. This method firstly use frame differencing method priorityly, background differencing method complementary. Then use an iteration threshold segmentation method to filter out the noise and the background image is updated real-time. Completed multi-lanes traffic detection, got many groups of data and calculated accuracy. The simulation experiment shows that this method can improve the accuracy of detection effectively, it is simple and feasible.
机译:研究交通流量准确度检测问题的优化。对于移动目标,速度和外部环境是影响交通流检测的主要因素。容易引起交通流检测的漏检和误判。为了克服传统的帧差分法和背景差分法在单独使用时的不足,本文通过现有算法提出了一种基于帧差分法和背景差分法融合的智能交通检测方法。该方法首先优先使用帧差分方法,背景差分方法是互补的。然后使用迭代阈值分割方法滤除噪声,并实时更新背景图像。完成多车道交通检测,获取多组数据并计算出准确性。仿真实验表明,该方法可以有效提高检测精度,简单可行。

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