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Classification with NormalBoost- Case Study Traffic Sign Classification
Dalarna University, School of Technology and Business Studies, Computer Engineering.ORCID iD: 0000-0002-1429-2345
2012 (English)In: Journal of Intelligent Systems, ISSN 2191-026X, Vol. 21, no 1, 25-43 p.Article in journal (Refereed) Published
Abstract [en]

NormalBoost is a new boosting algorithm which is capable of classifying a multi-dimensional binary class dataset. It adaptively combines several weak classifiers to form a strong classifier. Unlike many boosting algorithms which have high computation and memory complexities, NormalBoost is capable of classification with low complexity. The purpose of this paper is to present NormalBoost as a framework which establishes a platform to solve classification problems. The approach was tested with a dataset which was extracted automatically from real-world traffic sign images. The dataset contains both images of traffic sign borders and speed limit pictograms. This framework involves the computation of Haar-like features of these images and then employs the NormalBoost classifier to classify these traffic signs. The total number of images which were classified was 6500 binary images. A -fold validation was invoked to check the validity of the classification which resulted in a classification rate of 98.4% and 98.9% being achieved for these two databases. This framework is distinguished by its invariance to in-plane rotation of the images under consideration. Experiments show that the classification rate remains almost constant when traffic sign images with different angles of rotations were tested.

Place, publisher, year, edition, pages
Berlin: De Gruyter , 2012. Vol. 21, no 1, 25-43 p.
Keyword [en]
Pattern recognition; Classification; Boosting; Traffic Sign Recognition
Research subject
Komplexa system - mikrodataanalys
Identifiers
URN: urn:nbn:se:du-6477DOI: 10.1515/jisys-2012-0001OAI: oai:dalea.du.se:6477DiVA: diva2:520604
Available from: 2012-04-01 Created: 2012-04-01 Last updated: 2016-02-12Bibliographically approved

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CiteExportLink to record
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Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • chicago-author-date
  • chicago-note-bibliography
  • Other style
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Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
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  • asciidoc
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