Mean shift for accurate license plate localization

Wenjing Jia, Huaifeng Zhang, Xiangjian He, Massimo Piccardi

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

61 Citations (Scopus)

Abstract

This paper presents a region-based algorithm for accurate license plate localization, where mean shift is utilized to filter and segment color vehicle images into candidate regions. Three features are extracted in order to decide whether a candidate region represents a real license plate, namely, rectangularity, aspect ratio, and edge density. Then, the Mahalanobis classifier is used with respect to above three features to classify license plate regions and non-license plate regions. Experimental results show that the proposed algorithm produces high robustness and accuracy.

Original languageEnglish
Title of host publicationITSC`05
Subtitle of host publication2005 IEEE Intelligent Conference on Transportation Systems, Proceedings
Pages566-571
Number of pages6
DOIs
Publication statusPublished - 2005
Externally publishedYes
Event8th International IEEE Conference on Intelligent Transportation Systems - Vienna, Austria
Duration: 13 Sep 200516 Sep 2005

Publication series

NameIEEE Conference on Intelligent Transportation Systems, Proceedings, ITSC
Volume2005

Conference

Conference8th International IEEE Conference on Intelligent Transportation Systems
Country/TerritoryAustria
CityVienna
Period13/09/0516/09/05

ASJC Scopus subject areas

  • Automotive Engineering
  • Mechanical Engineering
  • Computer Science Applications

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