Maximally Stable Extremal Region Marking-Based Railway Track Surface Defect Sensing

Abstract

Railway track monitoring is a challenging task to avoid railway accidents due to track failures. There are lot many issues involved in the railway accidents but the major involvement is the use of defective railway tracks. The aim of this paper is to present a novel visual inspection technique for detection, marking, and visualization of defected portion in railway tracks. In this paper, maximally stable extremal region technique is used to identify and visualize the geometrical features of the defected regions on the rail head surface in railway track images. Here, three classes of surface defects have been taken. The results are very promising and comprise all the aspects.