Traffic Peak Period Detection from an Image Processing View
Traffic Peak Period Detection from an Image Processing View
复制标题
从图像处理视图检测流量高峰期
DOI：
10.1155/2018/2097932
复制
发表时间：
2018-01-01
影响因子：
2.3
通讯作者：
Yuan, Shangcao
中科院分区：
文献类型：
--
作者：
Xiao, Jianli;Li, Hang;Yuan, Shangcao
交通高峰期检测对于交通流的诱导和控制具有重要意义。交通高峰期检测的最常见方法是基于数据分析。他们取得了良好的业绩。然而，检测过程不够直观。除此之外，这些方法的准确性还需要进一步提高。本文从图像处理的角度出发，引入了角点检测中的锐度概念来检测交通高峰期。该方法将交通高峰期检测问题转化为显著点检测问题，并利用图像处理策略解决该问题。首先，利用速度数据生成速度曲线图像。利用该图像，采用显著点检测的方法来获得峰值点候选。如果一个候选者具有最低速度值，则该候选者是峰值点。最后，将峰值点对应的时间以一定的时间间隔前后移动，得到峰值周期。实验结果表明，该方法具有较高的准确率。更重要的是，由于该方法从图像处理的角度解决了交通高峰时段的检测问题，因此具有更强的直观性。
Traffic peak period detection is very important for the guidance and control of traffic flow. Most common methods for traffic peak period detection are based on data analysis. They have achieved good performance. However, the detection processes are not intuitional enough. Besides that, the accuracy of these methods needs to be improved further. From an image processing view, we introduce a concept in corner detection, sharpness, to detect the traffic peak periods in this paper. The proposed method takes the traffic peak period detection problem as a salient point detection problem and uses the image processing strategies to solve this problem. Firstly, it generates a speed curve image with the speed data. With this image, the method for detection of salient points is adopted to obtain the peak point candidates. If one candidate has the lowest speed value, this candidate is the peak point. Finally, the peak period is gotten by moving forward and backward the corresponding time of the peak point with a time interval. Experimental results show that the proposed method has achieved higher accuracy. More importantly, as the proposed method solves the traffic peak period detection problem from an image processing view, it has more intuition.