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
Invariant road sign recognition with fuzzy ARTMAP and zernike moments
Dalarna University, School of Technology and Business Studies, Computer Engineering.ORCID iD: 0000-0002-1429-2345
Dalarna University, School of Technology and Business Studies, Computer Engineering.
2007 (English)In: 2007 IEEE Intelligent Vehicles Symposium, vols 1-3, 2007, Vol. 1-3, p. 1-6Conference paper, Published paper (Refereed)
Abstract [en]

In this paper, a novel approach to recognize road signs is developed. Images of road signs are collected by a digital camera mounted in a vehicle. They are segmented using colour information and all objects which represent signs are extracted, normalized to 36x36 pixels, and used to train a Fuzzy ARTMAP neural network by calculating Zernike moments for these objects as features. Sign borders and pictograms are investigated in this study. Zernike moments of sign borders and speed-limit signs of 210 and 150 images are calculated as features. A fuzzy ARTMAP is trained directly with features, or by using PCA for dimension reduction, or by using LDA algorithm as dimension reduction and data separation algorithm. Two Fuzzy ARTMAP Neural Networks are trained. The first NN determines the class of the sign from the shape of its border and the second one determines the sign itself from its pictogram. Training and testing of both NNs is done offline by using still images. In the online mode, the system loads the Fuzzy ARTMAP Neural Networks, and performs recognition process. An accuracy of about 99% is achieved in sign border recognition and 96% for Speed-Limit recognition.

Place, publisher, year, edition, pages
2007. Vol. 1-3, p. 1-6
Keywords [en]
traffic sign recognition, recognition, fuzzy ARTMAP, zernike moments
National Category
Computer and Information Sciences
Identifiers
URN: urn:nbn:se:du-2772ISI: 000252173600001OAI: oai:dalea.du.se:2772DiVA, id: diva2:521748
Conference
IEEE-IV2007 , Istanbul, Turkey, 13-15 June, 2007
Available from: 2007-05-07 Created: 2007-05-07 Last updated: 2018-01-12Bibliographically approved

Open Access in DiVA

No full text in DiVA

Authority records BETA

Fleyeh, Hasan

Search in DiVA

By author/editor
Fleyeh, HasanDougherty, Mark
By organisation
Computer Engineering
Computer and Information Sciences

Search outside of DiVA

GoogleGoogle Scholar

urn-nbn

Altmetric score

urn-nbn
Total: 579 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