Change search
ReferencesLink to record
Permanent link

Direct link
Klassificering av hastighetsskyltar
Blekinge Institute of Technology, School of Engineering, Department of Signal Processing.
Blekinge Institute of Technology, School of Engineering, Department of Signal Processing.
2006 (English)Independent thesis Advanced level (degree of Master (One Year))Student thesisAlternative title
Classification of speed signs (Swedish)
Abstract [en]

Many people are involved in severe traffic related accident every year. Many of these accidents are strongly linked to too high speed. One way to decrease the speed transgressions and the number of accidents could be to implement a system that help the driver keeping the current speed limit. This thesis presents a method for classifying speed signs using computer vision. The classifier is a part of a system for speed tracking and notifying. This system assists a driver by notifying him/her of the current speed limit. This is done by computer vision, i.e. a camera connected to a computer reads the current trac environment and the frames are processed by the computer. A computer vision system is commonly composed by a detector and a classifier. The detector scans the frames from the camera and locates possible speed signs. The possible speed sign locations are passed to the classifier. The classifiers task is to decide if the possible location contains a speed sign and if it does contain a speed sign, to proclaim its speed. The classifier in this thesis is based on cross correlation. The algorithm is evaluated against a database, which includes images with coordinates for speed signs marked by hand. If the weather conditions are not to extreme and if the detector has good accuracy the classifier will make the right decision in close to 100% of the cases.

Place, publisher, year, edition, pages
2006. , 71 p.
Keyword [en]
Image Processing, Signal Processing, Computer Vision
National Category
Signal Processing
URN: urn:nbn:se:bth-4036Local ID: diva2:831355
Available from: 2015-04-22 Created: 2006-08-24 Last updated: 2015-06-30Bibliographically approved

Open Access in DiVA

fulltext(3214 kB)107 downloads
File information
File name FULLTEXT01.pdfFile size 3214 kBChecksum SHA-512
Type fulltextMimetype application/pdf

By organisation
Department of Signal Processing
Signal Processing

Search outside of DiVA

GoogleGoogle Scholar
Total: 107 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

Total: 32 hits
ReferencesLink to record
Permanent link

Direct link