Machine vision for automated inspection of railway traffic recordings

For the 9000 train accidents reported each year in the European Union [1], the Recording Strip (RS) and Filling-Card (FC) related to the train activities represent the only usable evidence for SNCF (the French railway operator) and most of National authorities. More precisely, the RS contains information about the train journey, speed and related Driving Events (DE) such as emergency brakes, while the FC gives details on the departure/arrival stations. In this context, a complete checking for 100% of the RS was recently voted by French law enforcement authorities (instead of the 5% currently performed), which raised the question of an automated and efficient inspection of this huge amount of recordings. To do so, we propose a machine vision prototype, constituted with cassettes receiving RS and FC to be digitized. Then, a video analysis module firstly determines the type of RS among eight possible types; time/speed curves are secondly extracted to estimate the covered distance, speed and stops, while associated DE are finally detected using convolution process. A detailed evaluation on 15 RS (8000 kilometers and 7000 DE) shows very good results (100% of good detections for the type of band, only 0.28% of non detections for the DE). An exhaustive evaluation on a panel of about 100 RS constitutes the perspectives of the work.