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出 处:《计算机系统应用》2016年第7期187-191,共5页Computer Systems & Applications
摘 要:基于虚拟检测线的车辆计数算法不可避免地会出现漏检和误检问题.针对这一问题,提取并结合了两种图像信息:目标与检测线相对位置信息和检测线像素值变化信息,提出了一种车流量分割计数方法用于提高准确率.首先确定车辆和检测线的相对位置,然后结合检测线上图像像素特征的变化规律对车辆进行分割计数.开发了一个测试系统验证本算法的实际效果,对多种不同场景下采集的视频进行了测试和结果分析.实验结果表明,在白天情况下,本算法在实时性和准确性方面都达到了理想的效果,各车道的准确率均在95%以上;但在条件恶劣的夜间场景下,准确率略有下降,需在下一步工作中做深入研究.The vehicle counting algorithm based on virtual line inevitably exists the possibility of missing and error. Concerning this issue, this paper extracts and combines two types of image information- the virtual lines' relative positions with the objects and its pixel value variance, then a new vehicle segmentation and counting method is proposed. First, it determines the relative positions between the objects and the virtual lines, and combines with the variance of virtual lines' pixel value. With these information, it can improves the accuracy of the traffic flow by means of dividing vehicles. A testing system is developed for testing the performance of the method. The system has run in some kinds of weather, and its result is analyzed. The results show that the method has excellent performance both in real-time and accuracy in the daytime and the accuracy was above 95% for each lane of traffic. But the performance in the nighttime may not be optimal. Therefore, improvement is planned to make during following research.
关 键 词:智能交通系统 虚拟检测线 车流量检测 像素值变化
分 类 号:TP391.41[自动化与计算机技术—计算机应用技术]
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