Intelligent Machine Vision Based Railway Infrastructure Inspection and Monitoring Using Uav

Abstract

Traditionally, railway inspection and monitoring are considered a crucial aspect of the system and are done by human inspectors. Rapid progress of the machine vision-based systems enables automated and autonomous rail track detection and railway infrastructure monitoring and inspection with flexibility and ease of use. In recent years, several prototypes of vision based inspection system have been proposed, where most have various vision sensors mounted on locomotives or wagons. This paper explores the usage of the UAVs (drones) in railways and computer vision based monitoring of railway infrastructure. Employing drones for such monitoring systems enables more robust and reliable visual inspection while providing a cost effective and accurate means for monitoring of the tracks. By means of a camera placed on a drone the images of the rail tracks and the railway infrastructure are taken. On these images, the edge and feature extraction methods are applied to determine the rails. The preliminary obtained results are promising.

Railway Tracks Detection of Railways Based On Computer Vision Technique and GNSS Data

“…The results for gauge measurements were reasonable for each image separately. On the other hand, Banic et al [3] suggested an image processing algorithm with advanced drone imagery system for automated railway tracks monitoring and detection. Results from this method depends primarily on canny edge detectors applied on captured images to detect rail lines and classify the detected edges [4].…”

UAVs in rail damage image diagnostics supported by deep-learning networks

“…Split defects are vertical defects in the rail head edge and, in extreme cases, horizontal defects in the entire head. It seems natural to use one of the standard edge detection algorithms, or more complex ones like [17,18]. The effectiveness of the above methods in terms of their use for split defects was also checked, but they proved to be ineffective.…”

Rail Track Detection and Projection-Based 3D Modeling from UAV Point Cloud

“…Singh et al [ 23 ] applied edge detection algorithms in UAV images to identify rail lines and calculated the geometric parameter of the rail gauge. Additionally, in 2019, Banic et al, by processing the video frames taken by a UAV using the edge detection operator and the K-nearest neighbor (KNN) classifier, identified rail tracks for automatic inspection [ 24 ]. To the best of our knowledge, there has been no previous study on the reconstruction of rail tracks using point clouds obtained from photogrammetric methods and the use of UAVs.…”