Moving-Vehicle Identification Based on Hierarchical Detection Algorithm
Moving-Vehicle Identification Based on Hierarchical Detection Algorithm
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DOI：
10.3390/su14010264
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发表时间：
2021-12
期刊：
影响因子：
3.9
通讯作者：
Zhifa Yang;Y. Zhu;Haodong Zhang;Zhuo Yu;Shiwu Li;Chao Wang
中科院分区：
文献类型：
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作者：
Zhifa Yang;Y. Zhu;Haodong Zhang;Zhuo Yu;Shiwu Li;Chao Wang
车辆检测方法在驾驶员辅助系统中起着重要的作用。因此，提高检测算法的实时性是非常重要的。目前最流行的方法是基于滑动窗口搜索的扫描方法，从待检测图像中检测出车辆。然而，现有的滑动窗口检测算法存在计算量大、实时性差等缺点，无法在运动过程中真实的实时检测到目标车辆。因此，本文提出了一种改进的分层滑动窗口检测算法，用于真实的实时检测运动车辆。通过提取感兴趣区域，对感兴趣区域进行分层，设置每层检测窗口的最大值和最小值，采用延时处理方法消除分层产生的闪烁帧，得到适合运动的方法：车辆的实时检测算法，即分层滑动窗口检测算法。实验表明，分层越多，所需时间越长，当检测层数大于7时，时间变化率显著增加。随着层数的减少，检测准确率也降低，导致误报的现象。因此，确定将图像分为7层时才能满足真实的时间和准确性的要求。从实验中可以看出，当待检测图像分为7层，检测窗口的最大值和最小值分别为30 × 30和250 × 250时，生成的子窗口数是原滑动窗口检测算法的1/37，执行时间仅为原滑动窗口检测算法的1/3。这说明分层滑动窗口检测算法比原有的滑动窗口检测算法具有更好的实时性。
The vehicle detection method plays an important role in the driver assistance system. Therefore, it is very important to improve the real-time performance of the detection algorithm. Nowadays, the most popular method is the scanning method based on sliding window search, which detects the vehicle from the image to be detected. However, the existing sliding window detection algorithm has many drawbacks, such as large calculation amount and poor real-time performance, and it is impossible to detect the target vehicle in real time during the motion process. Therefore, this paper proposes an improved hierarchical sliding window detection algorithm to detect moving vehicles in real time. By extracting the region of interest, the region of interest is layered, the maximum and minimum values of the detection window in each layer are set, the flashing frame generated by the layering is eliminated by the delay processing method, and a method suitable for the motion is obtained: the real-time detection algorithm of the vehicle, that is, the hierarchical sliding window detection algorithm. The experiments show that the more layers are divided, the more time is needed, and when the number of detection layers is greater than 7, the time change rate increases significantly. As the number of layers decreases, the detection accuracy rate also decreases, resulting in the phenomenon of a false positive. Therefore, it is determined to meet the requirements of real time and accuracy when the image is divided into 7 layers. It can be seen from the experiment that when the images to be detected are divided into 7 layers and the maximum and minimum values of detection windows are 30 × 30 and 250 × 250, respectively, the number of sub-windows generated is one thirty-seventh of the original sliding window detection algorithm, and the execution time is only one-third of the original sliding window detection algorithm. This shows that the hierarchical sliding window detection algorithm has better real-time performance than the original sliding window detection algorithm.