Missing Rail Fastener Detection Based on Machine Vision Method

Yongzhi Min, Benyu Xiao, Hongfeng Ma, Biao Yue

2018

Abstract

Rail fastener missing detection is an important part of railway daily inspection, according to the need of modern railway automatic detection, a method of rail fastener missing detection based on template matching is proposed in this paper. Firstly, in order to deal with the interference of environmental light, according to the basic principle of machine vision, a simple rail inspection car is designed for image acquisition. Secondly, according to the characteristics of the track image, the rail fastener area is located by using the mutation information of the image. Then, through the establishment of template, test images are matched with the template image, when the matching degree between test images and template images is low, it is need to detect the occlusion area of the test image and if there is a occlusion in the test image, remove the occlusion area from the test image and sample images to obtain new sample images and test image. Finally, the minimum distance classifier is used to detect the missing rail fastener. Simulation results show that the correct detection rate of this algorithm is 93.7% and the average detection time of each image is 385.74 ms, providing a reference for real-time detection of railway line.

Paper Citation

in Harvard Style

Min Y., Xiao B., Ma H. and Yue B. (2018). Missing Rail Fastener Detection Based on Machine Vision Method.In 3rd International Conference on Electromechanical Control Technology and Transportation - Volume 1: ICECTT, ISBN 978-989-758-312-4, pages 119-124. DOI: 10.5220/0006966101190124

in Bibtex Style

@conference{icectt18,
author={Yongzhi Min and Benyu Xiao and Hongfeng Ma and Biao Yue},
title={Missing Rail Fastener Detection Based on Machine Vision Method},
booktitle={3rd International Conference on Electromechanical Control Technology and Transportation - Volume 1: ICECTT,},
year={2018},
pages={119-124},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006966101190124},
isbn={978-989-758-312-4},
}

in EndNote Style

TY - CONF

JO - 3rd International Conference on Electromechanical Control Technology and Transportation - Volume 1: ICECTT,
TI - Missing Rail Fastener Detection Based on Machine Vision Method
SN - 978-989-758-312-4
AU - Min Y.
AU - Xiao B.
AU - Ma H.
AU - Yue B.
PY - 2018
SP - 119
EP - 124
DO - 10.5220/0006966101190124