du.sePublications
Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • chicago-author-date
  • chicago-note-bibliography
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Machine vision for analysing the position of fastening nails on wooden railway sleepers
Dalarna University, School of Technology and Business Studies, Computer Engineering.
Dalarna University, School of Technology and Business Studies, Computer Engineering.
2011 (English)In: Signal and Image Processing, 2011 / [ed] Rao, K.R., Dallas, Texas, USA, 2011Conference paper, Oral presentation with published abstract (Refereed)
Abstract [en]

Wooden railway sleeper inspections in Sweden and to a large extent elsewhere are carried out manually by a human operator; visual inspection being the most common approach. Manually inspecting railway sleepers is slow and time consuming. Machine vision algorithms investigating surface cracks on the sleeper and sinking of the metal plate have been studied for the purpose of automating the task. In this particular article, information concerning how far the fastening nail has lifted out of position is investigated with an aim of using such information while assessing the condition of the sleeper. Laser beams incident on the sleeper have been used to highlight the geometrical form of the sleeper/plate/nail complex. Digital images of the nail were acquired mimic human visual capabilities. Appropriate image analysis techniques were applied to further process the images and necessary features were extracted. Results of unsupervised learning, achieved in the current work indicate that expectation maximization algorithm produced reliable results.

Place, publisher, year, edition, pages
Dallas, Texas, USA, 2011.
Keywords [en]
Wooden railway sleepers, Machine vision, Condition Monitoring, Laser beam, Clustering, Unsupervised learning
National Category
Engineering and Technology
Research subject
Komplexa system - mikrodataanalys, Automatisk inspektion av järnvägsslipers
Identifiers
URN: urn:nbn:se:du-6031DOI: 10.2316/P.2011.759-051ISBN: 978-0-88986-918-9 (print)OAI: oai:dalea.du.se:6031DiVA, id: diva2:522440
Conference
IASTED conference on Signal and Image processing , Dallas, Texas, USA, 14-16 December, 2011
Available from: 2011-11-01 Created: 2011-11-01 Last updated: 2012-08-02Bibliographically approved

Open Access in DiVA

No full text in DiVA

Other links

Publisher's full text

Search in DiVA

By author/editor
Yella, SirilDougherty, Mark
By organisation
Computer Engineering
Engineering and Technology

Search outside of DiVA

GoogleGoogle Scholar

doi
isbn
urn-nbn

Altmetric score

doi
isbn
urn-nbn
Total: 682 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • chicago-author-date
  • chicago-note-bibliography
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf