基于计算机视觉的交通流量计数算法

Huasheng Zhu, Chenguang Xu, Fan Li
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引用次数: 3

摘要

提出了一种基于改进的单高斯模型的车辆检测与交通量统计算法。该算法主要包括运动目标检测、阴影抑制和流量统计三个部分。首先,采用改进的背景初始化方法,利用单高斯模型检测运动目标;然后,提出了一种在RGB特征空间中阴影抑制的计算方法。最后,对虚拟车道区域的交通量进行统计。对该算法进行了两次实验。结果表明,该算法能够快速检测车辆,具有较高的识别率。它在实际条件下可以很好地工作。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The Traffic Volume Count Algorithm Based on Computer Vision
This paper proposes a vehicle detection and traffic volume statistics algorithm Based on an improved single Gaussian model. This algorithm contains three major sections, which are moving target detection, shadows suppression and traffic volume count. Firstly, with an improved background initialization method, the paper detects the moving target by using the single Gaussian model. Then, a computational method of Shadows suppression is presented in the RGB feature space. Finally, the traffic volume is counted in the virtual areas of lanes. Two experiments are performed on the algorithm. The results show that the algorithm can detect vehicle quickly and have a higher recognition rate. It can works well in the actual conditions.
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