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Traffic Signs Color Detection and Segmentation in Poor Light Conditions
Dalarna University, School of Technology and Business Studies, Computer Engineering.ORCID iD: 0000-0002-1429-2345
2005 (English)In: Machine Vision Applications (MVA2005), Tsukuba Science City, 2005Conference paper, Published paper (Refereed)
Abstract [en]

This paper presents a new algorithm for color detection and segmentation of road signs in poor light conditions. The images were taken by a digital camera mounted in a car. The RGB channels of the digital images were enhanced separately by histogram equalization, and then a color constancy algorithm was applied to extract the true colors of the sign. The resultant image was then converted into HSV color space, and segmented to extract the colors of the road signs. The method was tested on outdoor images in different poor light conditions such as fog and snow, and they show high robustness. This project is part of the research taking place at Dalarna University - Sweden in the field of the Intelligent Transport Systems (ITS).

Place, publisher, year, edition, pages
Tsukuba Science City, 2005.
Keywords [en]
Color segmentation, color constancy, histogram equalization, color detection, road signs, outdoor images.
National Category
Transport Systems and Logistics
Identifiers
URN: urn:nbn:se:du-1025OAI: oai:dalea.du.se:1025DiVA, id: diva2:521402
Conference
Machine Vision Applications (MVA2005), Tsukuba Science City, 2005
Available from: 2005-05-02 Created: 2005-05-02 Last updated: 2019-10-16Bibliographically approved

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Type fulltextMimetype application/pdf

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Fleyeh, Hasan

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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