Machine Vision For Condition Monitoring Vegetation On Railway Embankments

Research Output

National Railway Administration in Northern Europe do not employ systematic procedures in monitoring the current state of vegetation to form the basis of maintenance decision making. Current day vegetation maintenance is largely based on human visual estimates. this paper investigates a machine vision (MV) approach to be able to automatically quantify the amount of vegetation on a given railway section. An investigation assessing the reliability of human estimates is also conducted along the same railway section.

Date:

17 September 2014
Publication Status:

Published
Library of Congress:

TA Engineering (General). Civil engineering (General)
Dewey Decimal Classification:

624 Civil engineering
Funders:

Edinburgh Napier Funded

http://researchrepository.napier.ac.uk/output/968499 <p>Nyberg, R., Gupta, N., Yella, S. & Dougherty, M. (2014). Machine Vision For Condition Monitoring Vegetation On Railway Embankments. In <i>Proceedings of 6th IET Conference on Railway Condition Monitoring, RCM</i>, 1-7. ISBN 978-1-84919-913-1</p>

Citation

Nyberg, R., Gupta, N., Yella, S. & Dougherty, M. (2014). Machine Vision For Condition Monitoring Vegetation On Railway Embankments. In Proceedings of 6th IET Conference on Railway Condition Monitoring, RCM, 1-7. ISBN 978-1-84919-913-1