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Road and Traffic Signs Recognition using Vector Machines
Dalarna University, School of Technology and Business Studies, Computer Engineering.
2006 (English)Independent thesis Advanced level (degree of Master (Two Years))Student thesis
Abstract [en]

Intelligent Transportation System (ITS) is a system that builds a safe, effective and integrated transportation environment based on advanced technologies. Road signs detection and recognition is an important part of ITS, which offer ways to collect the real time traffic data for processing at a central facility. This project is to implement a road sign recognition model based on AI and image analysis technologies, which applies a machine learning method, Support Vector Machines, to recognize road signs. We focus on recognizing seven categories of road sign shapes and five categories of speed limit signs. Two kinds of features, binary image and Zernike moments, are used for representing the data to the SVM for training and test. We compared and analyzed the performances of SVM recognition model using different features and different kernels. Moreover, the performances using different recognition models, SVM and Fuzzy ARTMAP, are observed.

Place, publisher, year, edition, pages
Borlänge, 2006. , 100 p.
Keyword [en]
Road sign recognition, support vector machines
Identifiers
URN: urn:nbn:se:du-2281OAI: oai:dalea.du.se:2281DiVA: diva2:518097
Uppsok
Technology
Supervisors
Available from: 2006-09-04 Created: 2006-09-04 Last updated: 2012-04-24Bibliographically approved

Open Access in DiVA

fulltext(1181 kB)2107 downloads
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CiteExportLink to record
Permanent link

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