高斯算法在道路交通车流量统计中的应用

摘要

In this paper, in view of the low accuracy and difficulty of the measurement of roadway vehicle flow volume, we used the Gauss modeling algorithm to generate the background image, and then constantly updated the image according to the changes in parameterization. Then we introduced the working mechanism of the algorithm and at the end, through an experiment, proved the its accuracy and effectiveness in improving logistics efficiency of the roadway vehicles.%针对道路交通车流量测量难和精度低的问题，采取高斯建模算法生成背景图像，并根据参数变化不断更新背景。利用背景差分算法得到被检测车辆的前景图像对前景目标图像采用阴影消除算法和形态学处理后再进行道路车流量计算，避免了由光照和噪声造成的重检和漏检对统计结果的影响。实验结果表明，设计的算法能够准确地分离出前景图像中的被检测车辆目标，在对道路进行的50min车流量统计中检测准确率高达98.71%，为保证路面车辆畅通行驶提供了有力的数据支持，有助于大大提高道路车辆的物流效率。