The color identification of automobiles for video surveillance

Yu Chen Wang, Chen Ta Hsieh, Chin Chuan Han, Kuo Chin Fan

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

8 Scopus citations

Abstract

Color identification of automobiles plays a significant in intelligent transportation systems (ITS). In this paper, a novel scheme for color identification of automobile is proposed using the taillight detection and a template matching module. The taillights of cars are detected to find the valid regions of interested (ROIs) for color identification. The color feature vectors generated by 3 by 3 neighboring pixels are classified by a template matching strategy. Seven classes, red, yellow, blue, green, black, white, and gray, are identified in this work. Experimental results have been conducted to show the validity of the proposed method. The averaged accuracy rate 81.71% is achieved and the performance of this scheme is up to 20 frames per second.

Original languageEnglish
Title of host publication2011 Carnahan Conference on Security Technology, ICCST 2011
DOIs
StatePublished - 2011
Event2011 IEEE International Carnahan Conference on Security Technology, ICCST 2011 - Barcelona, Spain
Duration: 18 Oct 201121 Oct 2011

Publication series

NameProceedings - International Carnahan Conference on Security Technology
ISSN (Print)1071-6572

Conference

Conference2011 IEEE International Carnahan Conference on Security Technology, ICCST 2011
Country/TerritorySpain
CityBarcelona
Period18/10/1121/10/11

Keywords

  • color identification of automobiles
  • color template matching algorithm
  • Intelligent transportation system
  • region of interest
  • taillight detection algorithm

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