Segmenting characters from license plate images with little prior knowledge

Wenjing Jia, Xiangjian He, Qiang Wu

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

5 Citations (Scopus)

Abstract

In this paper, to enable a fast and robust system for automatically recognizing license plates with various appearances, new and simple but efficient algorithms are developed to segment characters from extracted license plate images. Our goal is to segment characters properly from a license plate image region. Different from existing methods for segmenting degraded machine-printed characters, our algorithms are based on very weak assumptions and use no prior knowledge about the format of the plates, in order for them to be applicable to wider applications. Experimental results demonstrate promising efficiency and flexibility of the proposed scheme.

Original languageEnglish
Title of host publicationProceedings - 2010 Digital Image Computing
Subtitle of host publicationTechniques and Applications, DICTA 2010
Pages220-226
Number of pages7
DOIs
Publication statusPublished - 2010
Externally publishedYes
EventInternational Conference on Digital Image Computing: Techniques and Applications, DICTA 2010 - Sydney, NSW, Australia
Duration: 1 Dec 20103 Dec 2010

Publication series

NameProceedings - 2010 Digital Image Computing: Techniques and Applications, DICTA 2010

Conference

ConferenceInternational Conference on Digital Image Computing: Techniques and Applications, DICTA 2010
Country/TerritoryAustralia
CitySydney, NSW
Period1/12/103/12/10

ASJC Scopus subject areas

  • Computational Theory and Mathematics
  • Computer Science Applications

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