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
Night time vehicle detection
Dalarna University, School of Technology and Business Studies, Computer Engineering.ORCID iD: 0000-0002-1429-2345
2012 (English)In: Journal of Intelligent Systems, ISSN 2191-026X, Vol. 21, no 2, 143-165 p.Article in journal (Refereed) Published
Abstract [en]

Night driving is one of the major factors which affects traffic safety. Althoughdetecting oncoming vehicles at night time is a challenging task, it may improve trafficsafety. If the oncoming vehicle is recognised in good time, this will motivate drivers tokeep their eyes on the road. The purpose of this paper is to present an approach to detectvehicles at night based on the employment of a single onboard camera. This system isbased on detecting vehicle headlights by recognising their shapes via an SVM classifierwhich was trained for this purpose. A pairing algorithm was designed to pair vehicleheadlights to ensure that the two headlights belong to the same vehicle. A multi-objecttracking algorithm was invoked to track the vehicle throughout the time the vehicle isin the scene. The system was trained with 503 single objects and tested using 144 587single objects which were extracted from 1410 frames collected from 15 videos and 27moving vehicles. It was found that the accuracy of recognition was 97.9% and the vehiclerecognition rate was 96.3% which indicates clearly the high robustness attained by thissystem.

Place, publisher, year, edition, pages
Berlin: Walter de Gruyter, 2012. Vol. 21, no 2, 143-165 p.
Keyword [en]
Vehicle Detection; Object Tracking; SVM Shape Classification; Night Detection
National Category
Computer Systems
Research subject
Complex Systems – Microdata Analysis
Identifiers
URN: urn:nbn:se:du-10164DOI: 10.1515/jisys-2012-0007OAI: oai:DiVA.org:du-10164DiVA: diva2:532731
Available from: 2012-06-12 Created: 2012-06-12 Last updated: 2016-02-12Bibliographically approved

Open Access in DiVA

No full text

Other links

Publisher's full texthttp://www.degruyter.com/view/j/jisys

Search in DiVA

By author/editor
Fleyeh, Hasan
By organisation
Computer Engineering
Computer Systems

Search outside of DiVA

GoogleGoogle Scholar

Altmetric score

Total: 696 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