liu.seSearch for publications in DiVA
Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • oxford
  • 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
Vehicle Detection in Monochrome Images
Linköping University, Department of Electrical Engineering, Computer Vision. Linköping University, The Institute of Technology.
2008 (English)Independent thesis Advanced level (professional degree), 20 credits / 30 HE creditsStudent thesis
Abstract [en]

The purpose of this master thesis was to study computer vision algorithms for vehicle detection in monochrome images captured by mono camera. The work has mainly been focused on detecting rear-view cars in daylight conditions. Previous work in the literature have been revised and algorithms based on edges, shadows and motion as vehicle cues have been modified, implemented and evaluated. This work presents a combination of a multiscale edge based detection and a shadow based detection as the most promising algorithm, with a positive detection rate of 96.4% on vehicles at a distance of between 5 m to 30 m. For the algorithm to work in a complete system for vehicle detection, future work should be focused on developing a vehicle classifier to reject false detections.

Place, publisher, year, edition, pages
Institutionen för systemteknik , 2008. , 51 p.
Keyword [en]
vehicle detection, edge based detection, shadow based detection, motion based detection, mono camera system
National Category
Computer Vision and Robotics (Autonomous Systems)
Identifiers
URN: urn:nbn:se:liu:diva-11819ISRN: LiTH-ISY-EX--08/4148--SEOAI: oai:DiVA.org:liu-11819DiVA: diva2:18234
Subject / course
Computer Vision Laboratory
Presentation
(English)
Uppsok
Technology
Supervisors
Examiners
Available from: 2008-06-12 Created: 2008-06-12 Last updated: 2012-07-02Bibliographically approved

Open Access in DiVA

fulltext(6190 kB)1542 downloads
File information
File name FULLTEXT01.pdfFile size 6190 kBChecksum SHA-1
e94d6f20f83c37bf383af8ce2517e3a2f145899046e1046b98bb89b278beb3e93b0843df
Type fulltextMimetype application/pdf

By organisation
Computer VisionThe Institute of Technology
Computer Vision and Robotics (Autonomous Systems)

Search outside of DiVA

GoogleGoogle Scholar
Total: 1542 downloads
The number of downloads is the sum of all downloads of full texts. It may include eg previous versions that are now no longer available

urn-nbn

Altmetric score

urn-nbn
Total: 765 hits
CiteExportLink to record
Permanent link

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