Vision-based railway inspection system using multiple object detection and image registration

Abstract

Image processing and computer vision techniques have been utilized for safety and maintenance in the railway field. Although a lot of research has been proposed to automatically inspect a facility, most diagnosis for facility maintenance is still dependent on a manager’s subjective judgment. This paper presents a novel railway-inspection system using object detection and image subtraction based on registration. For accurate deformation and defect inspection, the proposed system compares a pair of two high-resolution images acquired by a laser scan camera equipped on a railway vehicle. The proposed system consists of three parts: i) object detection using classifiers learned by random forest, ii) facility position alignment using phase correlation matching, and iii) deformation and defect detection using image registration and subtraction. The proposed inspection system performs automatic inspections by detecting facilities and any deformed regions. Therefore, the proposed system can provide improvement of a maintenance system at a cost reduction. Copyrights © 2018 The Institute of Electronics and Information Engineers.