Verification of the Accuracy of Rail Joint Detection and Kilometer Estimation for Track Components Condition Evaluation System Using Smartphone Images

Abstract

Previous research has shown that when images acquired by smartphones are applied to the track component condition evaluation system under development, the system can accurately detect and identify the deterioration of wooden sleepers, PC sleepers, rail fastening systems, and other track components. However, the accuracy of rail joint detection and kilometer estimation has not been verified by using the developing system. In this study, images acquired by smartphones were applied to a track component condition evaluation system to verify the accuracy of rail joint detection and kilometerage estimation. As a result, it was found that the developing system was able to detect rail joints with high accuracy. On the other hand, the estimation error of the kilometerage was sometimes greater than that of the conventional method due to the failure to detect kilometerage post marker installed on concreate sleepers in some sections.