A comparison on histogram based image matching methods

Wenjing Jia, Huaifeng Zhang, Xiangjian He, Qiang Wu

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

15 Citations (Scopus)

Abstract

Using colour histogram as a stable representation over change in view has been widely used for object recognition. In this paper, three newly proposed histogram-based methods are compared with other three popular methods, including conventional histogram intersection (HI) method, Wong and Cheung's merged palette histogram matching (MPHM) method, and Gevers' colour ratio gradient (CRG) method. These methods are tested on vehicle number plate images for number plate classification. Experimental results disclose that, the CRG method is the best choice in terms of speed, and the GWHI method can give the best classification results. Overall, the CECH method produces the best performance when both speed and classification performance are concerned.

Original languageEnglish
Title of host publicationProceedings - IEEE International Conference on Video and Signal Based Surveillance 2006, AVSS 2006
PublisherIEEE Computer Society
Pages97-102
Number of pages6
ISBN (Print)0769526888, 9780769526881
DOIs
Publication statusPublished - 2006
Externally publishedYes
EventIEEE International Conference on Video and Signal Based Surveillance 2006, AVSS 2006 - Sydney, NSW, Australia
Duration: 22 Nov 200624 Nov 2006

Publication series

NameProceedings - IEEE International Conference on Video and Signal Based Surveillance 2006, AVSS 2006

Conference

ConferenceIEEE International Conference on Video and Signal Based Surveillance 2006, AVSS 2006
Country/TerritoryAustralia
CitySydney, NSW
Period22/11/0624/11/06

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition
  • Signal Processing
  • Electrical and Electronic Engineering

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