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An adaptive approach to detect warning traffic signs using som and windowed hough transform
Dalarna University, School of Technology and Business Studies, Computer Engineering.ORCID iD: 0000-0002-1429-2345
2011 (English)In: IASTED, Krete, 2011, 195-202 p.Conference paper, Published paper (Refereed)
Abstract [en]

Warning traffic signs represent an important group of traffic signs which indicate danger for road users. Detecting this group in good time may be helpful to avoid many fatal accidents. This paper presents a new approach to detecting warning traffic signs which is based on color segmentation using Self Organizing Maps and windowed Hough Transform. The proposed system is a standalone and adaptive which means that it works without any kind of training. This is due to the fact that color segmentation using SOM employs 1% of the image under investigation for the training and Hough transform is invoked to detect the shape of this group of traffic signs. Experiments conducted to check the robustness of this approach indicated that 95.6% of the traffic signs invoked for this test were successfully detected. This test was carried out under a wide range of environmental conditions and in different European countries.

Place, publisher, year, edition, pages
Krete, 2011. 195-202 p.
Keyword [en]
Traffic signs, color segmentation, hough transform, triangle detection, self organizing maps
Research subject
Komplexa system - mikrodataanalys
Identifiers
URN: urn:nbn:se:du-5659OAI: oai:dalea.du.se:5659DiVA: diva2:522317
Conference
SIPA 2011 , Krete, 22-24 June, 2011
Available from: 2011-08-08 Created: 2011-08-08 Last updated: 2016-02-12Bibliographically approved

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CiteExportLink to record
Permanent link

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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