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Robust Implementation for Circular Traffic Sign Recognition

  • Yuan Shui Huang*
  • , Meng Yin Fu
  • , Hong Bin Ma
  • *Corresponding author for this work
  • Beijing Institute of Technology

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

The design of traffic sign recognition (TSR) system has been a challenging practical problem for many years. The frequently used approaches involve color segmentation, shape analysis, and pictogram classification. To cope with the requirements of robustness and accuracy, we introduce a robust circular traffic sign detection approach consisting of a color enhancement method which utilizes the nature of Lab color space and a circle detector based on improved constrained fast radial symmetry transform. To effectively represent the pictogram of candidate sign, an informative data representation method, i.e., circular local binary pattern histogram, is presented for designing the traffic sign classifier through support vector machine. The system performance under extensive experiments has shown robust detection effects and outperforms existing approaches in terms of classification accuracy.

Original languageEnglish
Title of host publication2011 International Conference in Electrics, Communication and Automatic Control Proceedings
EditorsRan Chen
PublisherSpringer Science and Business Media Deutschland GmbH
Pages907-917
Number of pages11
ISBN (Print)9781441988485
DOIs
Publication statusPublished - 2012
EventInternational Conference in Electrics, Communication and Automatic Control, ECAC 2011 - Chongqing, China
Duration: 23 Jun 201124 Jun 2011

Publication series

NameLecture Notes in Electrical Engineering
Volume165 LNEE
ISSN (Print)1876-1100
ISSN (Electronic)1876-1119

Conference

ConferenceInternational Conference in Electrics, Communication and Automatic Control, ECAC 2011
Country/TerritoryChina
CityChongqing
Period23/06/1124/06/11

Keywords

  • Circular local binary pattern histogram
  • Fast radial symmetry transform
  • Support vector machine
  • Traffic sign recognition

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