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Analysis of Speed Sign Classification Algorithms Using Shape Based Segmentation of Binary Images
Blekinge Institute of Technology, Ronneby, Sweden.ORCID iD: 0000-0002-0535-1761
2009 (English)Conference paper, Published paper (Refereed)
Abstract [en]

Traffic Sign Recognition is a widely studied problem and its dynamic nature calls for the application of a broad range of preprocessing, segmentation, and recognition techniques but few databases are available for evaluation. We have produced a database consisting of 1,300 images captured by a video camera. On this database we have conducted a systematic experimental study. We used four different preprocessing techniques and designed a generic speed sign segmentation algorithm. Then we selected a range of contemporary speed sign classification algorithms using shape based segmented binary images for training and evaluated their results using four metrics, including accuracy and processing speed. The results indicate that Naive Bayes and Random Forest seem particularly well suited for this recognition task. Moreover, we show that two specific preprocessing techniques appear to provide a better basis for concept learning than the others.

Place, publisher, year, edition, pages
Munster: Springer, 2009.
Keyword [en]
road sign, classification, supervised learning
National Category
Computer Sciences
Identifiers
URN: urn:nbn:se:hj:diva-37960ISI: 000273458100148ISBN: 978-3-642-03766-5 (print)OAI: oai:DiVA.org:hj-37960DiVA: diva2:1159736
Conference
13th International Conference on Computer Analysis of Images and Patterns Munster, GERMANY, SEP 02-04, 2009
Note

Source: COMPUTER ANALYSIS OF IMAGES AND PATTERNS, PROCEEDINGS Book Series: Lecture Notes in Computer Science Volume: 5702 Pages: 1220-1227 Published: 2009

Available from: 2017-11-23 Created: 2017-11-23 Last updated: 2017-11-23Bibliographically approved

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Lavesson, Niklas

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CiteExportLink to record
Permanent link

Direct link
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