Track detection and gauge measurement are considered as crucial aspects of railway inspection systems. Traditionally, monitoring by human inspectors was done. Nowadays, computer vision-based systems are used due to their flexibility and ease of use. In recent years, various prototypes of vision based inspection system have been proposed, most have a camera mounted on carts or trains. Employing drones for such monitoring systems provides a cost effective and accurate means for monitoring tracks. This paper explores the possibilities of computer vision based monitoring through drone imagery. The experimental results ensure that the proposed method provides high reliability and accuracy.

Drones provide flexibility to operate at various heights and in adverse terrains where regular inspection methods cannot be applied.

Drone data contains various challenges such as rectification, referencing and ground sampling, that requires various preprocessing task . Despite this, monitoring through drones has several advantages such as it does not require separate tracks for data acquisition, thereby not hindering the schedule of trains. Further it is easy to implement in ground reality and is accurate and cost effective. Thus, it can be frequently used for monitoring any situation.