Abstract

Abstract. The maintenance of railway infrastructure requires detailed inspection of track assets including the rails, sleepers, fasteners, and tie plates. Current methods using total stations and measurement trains are costly and the subsequent data processing is often manual. A potent alternative is the use of Unmanned Aerial Vehicles (UAV) to investigate track asset deviations. However, the potential degree of automation and the overall accuracy is still very much the subject of ongoing research. In this work, a potential pipeline is investigated for the planimetric inspection of rails using UAV photogrammetry. Specifically, state-of-the-art line detectors such as Holistically-Nested Edge Detection, DexiNed, Segment Anything Model, and Mobile Line Segment Detection are combined with logical filtering to assess the localisation and gauge of the rails. The experiments indicate that the accuracy and detection rate are promising. Overall, the proposed method is a promising step towards affordable and safe railway infrastructure inspection.

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