Learning-based license plate detection in vehicle image database

Huaifeng Zhang, Wenjing Jia, Xiangjian He, Qiang Wu

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Abstract

This paper proposes a learning-based algorithm to detect license plates of vehicles from vehicle image database. There are three main contributions in this paper. The first contribution is to define a novel vertical edge map, which makes the image processing more effectively. The second contribution is to propose a learning-based cascade classifier composing of two kinds of sub-classifiers, which makes the system very robust. The third contribution is to experimentally estimate the parameter of scaling factor and chose an optimal one for the algorithm to seek a good balance between detection rate and processing time.

Original languageEnglish
Pages (from-to)228-243
Number of pages16
JournalInternational Journal of Intelligent Information and Database Systems
Volume1
Issue number2
DOIs
Publication statusPublished - 2007
Externally publishedYes

Keywords

  • AdaBoost
  • CBIR
  • cascade classifier
  • content-based image retrieval
  • license plate detection
  • vehicle image database

ASJC Scopus subject areas

  • Information Systems

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Zhang, H., Jia, W., He, X., & Wu, Q. (2007). Learning-based license plate detection in vehicle image database. International Journal of Intelligent Information and Database Systems, 1(2), 228-243. https://doi.org/10.1504/IJIIDS.2007.014952