Noval Railway Track Crack Detection System

The most cost-effective and efficient form of transportation for passengers, as well as for long-distance and suburban travel, is by train. The unreported cracks in railroad tracks and railroad track crossings are the causes of accidents on railroads. Hence, there is a requirement for a reliable, stable, and efficient railway track crack detection system. This work presents an innovative approach for automatic crack identification in railway tracks: the Railway Track Crack Detection System, which uses OpenCV. Utilizing digital photos taken by cameras along the route, the system makes use of OpenCV’s image processing features to perform functions like feature extraction, crack detection, and pre-processing. The algorithm precisely detects and locates cracks through contour analysis, augmentation, and filtering. The system contributes to improved railway safety and dependability by reducing the need for manual inspections, guaranteeing a quicker reaction to track faults, and integrating easily into current maintenance systems. Results from the experiments show how effective the system is in different situations.