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Machine vision for the automatic classification of images acquired from Non-destructive tests
Dalarna University, School of Technology and Business Studies, Computer Engineering.
2007 (English)Independent thesis Advanced level (degree of Master (Two Years))Student thesis
Abstract [en]

This project is based on Artificial Intelligence (A.I) and Digital Image processing (I.P) for automatic condition monitoring of sleepers in the railway track. Rail inspection is a very important task in railway maintenance for traffic safety issues and in preventing dangerous situations. Monitoring railway track infrastructure is an important aspect in which the periodical inspection of rail rolling plane is required. Up to the present days the inspection of the railroad is operated manually by trained personnel. A human operator walks along the railway track searching for sleeper anomalies. This monitoring way is not more acceptable for its slowness and subjectivity. Hence, it is desired to automate such intuitive human skills for the development of more robust and reliable testing methods. Images of wooden sleepers have been used as data for my project. The aim of this project is to present a vision based technique for inspecting railway sleepers (wooden planks under the railway track) by automatic interpretation of Non Destructive Test (NDT) data using A.I. techniques in determining the results of inspection.

Place, publisher, year, edition, pages
Borlänge, 2007. , 63 p.
Keyword [en]
Artificial intelligence; Non-destructive testing; Automatic data interpretation; Rail inspection; Rail transportation
Identifiers
URN: urn:nbn:se:du-2520OAI: oai:dalea.du.se:2520DiVA: diva2:518190
Uppsok
Technology
Supervisors
Available from: 2007-02-23 Created: 2007-02-23 Last updated: 2012-04-24Bibliographically approved

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CiteExportLink to record
Permanent link

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Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • 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