A Visual Inspection System for Rail Corrugation Based on Local Frequency Features

Abstract

Corrugation detection based on computer vision is a rapid and economical inspection technology, and it has attracted more and more attention from railway industry. This paper presents an effective corrugation detection system that includes an on-board image acquisition subsystem and a corrugation identification subsystem. In the corrugation identification subsystem, a track image captured by the on-board image acquisition subsystem is first segmented by the rail localization algorithm based on weighted projection profile. And then each column of the segmented rail image is represented by local frequency features and identified as corrugation line or not by a support vector machine (SVM). Lastly, the rail image is judged as corrugation by integrating the recognized corrugation lines. The experiment results show the precision and recall of the proposed corrugation detection system are 98.47% and 96.50%, respectively. They are 25% and 1% higher than those of traditional method. At the same time, the detection speed is doubly faster than that of the traditional method.