Catalano Ester, Coscetta Agnese, Cerri Enis, Cennamo Nunzio, Zeni Luigi, Minardo A
Appl Opt. 2021 May 1;60(13):3579-3584. doi: 10.1364/AO.422385.
In this paper, we demonstrate automatic vehicle detection and counting by processing data acquired using a phase-sensitive optical time-domain reflectometer (-OTDR) distributed optical fiber sensor. The acquired data are processed using the Hough transform, which detects the lines in the images formed by representing the acquired data in the space-time domain. A rough classification of the vehicles (heavy versus light vehicles) is also proposed, based on the amplitude of the vibration data along the detected lines. The method has been experimentally tested by performing -OTDR measurements along a telecommunication fiber cable running in a buried conduit along the state road SS18 (province of Salerno, Italy), opened to normal traffic. Comparison with ground-truth data, manually generated by inspecting video recordings, allowed us to estimate a vehicle detection success rate up to 73%, while heavy vehicles were fully detected.
在本文中，我们通过处理使用相敏光时域反射仪（-OTDR）分布式光纤传感器采集的数据，演示了车辆的自动检测和计数。使用霍夫变换对采集到的数据进行处理，该变换在通过将采集到的数据表示在时空域中形成的图像中检测线条。还基于沿检测到的线条的振动数据的幅度，提出了车辆的粗略分类（重型车辆与轻型车辆）。该方法已通过沿着意大利萨勒诺省SS18国道地下管道中铺设的通信光缆进行-OTDR测量进行了实验测试，该道路正常通车。与通过检查视频记录手动生成的地面真值数据进行比较，使我们能够估计车辆检测成功率高达73%，而重型车辆则被全部检测到。
