IIT Roorkee Develops “Computer Vision Approach” To Monitor Railway Track Health


Researchers at the Indian Institute of Technology, Roorkee, have developed computer vision approach for the monitoring of railway tracks using drones and satellite data with “a fast, accurate and cost-effective way of detecting various anomalies”.

The aim of the project is to provide some automated techniques for track inspection, which is carried out manually at present.

“Due to the course of time, rail track component come across various defects like: loose rail fasteners, rail cracks, rail burns, misplaced crossties, broken crossties, a problem with the joints, and defect at switches as well as less visually evident defects like shifting from the mathematical model of track geometry over time. In particular, a common problem in the railroad industry is the tendency of rails to deviate from their proper gauge,” Prof. Dharmendra Singh, Department of Electronics and Communication Engineering,  who is also the coordinator of RailTel and IIT Roorkee’s Centre of Excellence in Telecommunication, said.

“Computer Vision Approach and image processing on Drone data is a good alternative to monitor the railway track health in less time and it is also a very cost-effective system.“Some modules have already been developed which are giving quite satisfactory results and in some other modules like crack detection and all work is in progress and hopefully it will be completed soon, he added.

The objectives of the new technology are pre-processing of the data collected using a drone; creation of reasonable, simple, and fast computer vision algorithm that is capable of processing the experimental field data and finding railroad defects reliably; comparative evaluation of the performance of different algorithms and design schematics uncovering their better and worse features.


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