Vehicle Detection in Monochrome Images
Independent thesis Advanced level (professional degree), 20 credits / 30 HE creditsStudent thesis
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.
vehicle detection, edge based detection, shadow based detection, motion based detection, mono camera system
Computer Vision and Robotics (Autonomous Systems)
IdentifiersURN: urn:nbn:se:liu:diva-11819ISRN: LiTH-ISY-EX--08/4148--SEOAI: oai:DiVA.org:liu-11819DiVA: diva2:18234
Subject / course
Computer Vision Laboratory
Hedberg, OgnjanTjärnström, FredrikNordberg, Klas