Machine Vision For Condition Monitoring Vegetation On Railway Embankments

Nyberg, Roger; Gupta, Naren; Yella, Siril; Dougherty, Mark

Abstract

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.

Citation

Nyberg, R., Gupta, N., Yella, S., & Dougherty, M. (2014, September). Machine Vision For Condition Monitoring Vegetation On Railway Embankments. Presented at 6th IET Conference on Railway Condition Monitoring, RCM

• Conference Name: 6th IET Conference on Railway Condition Monitoring, RCM
• Start Date: Sep 17, 2014
• End Date: Sep 18, 2014
• Acceptance Date: Sep 17, 2014
• Publication Date: Sep 17, 2014
• Deposit Date: Jul 28, 2017
• Pages: 1-7
• Book Title: Proceedings of 6th IET Conference on Railway Condition Monitoring, RCM
• Chapter Number: n/a
• ISBN: 978-1-84919-913-1
• Keywords: Condition monitoring, machine vision, railway vegitation
• Public URL: http://researchrepository.napier.ac.uk/Output/968499