License plate localization based on a probabilistic model

Rami Al-Hmouz*, Subhash Challa

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

25 Citations (Scopus)

Abstract

Extraction of the license plate region is the challenging first step in the license plate recognition system. We propose a novel feature fusion concept for plate extraction. The image-feature extraction process is modeled as a feature-detection problem in noise. The geometric features are probabilistically modeled and detected under various detection thresholds. These detection results are then fused within the Bayesian framework to obtain the features for further processing. Along with a probabilistic model, a pixels voting algorithm is also tested through threshold variation.

Original languageEnglish
Pages (from-to)319-330
Number of pages12
JournalMachine Vision and Applications
Volume21
Issue number3
DOIs
Publication statusPublished - Apr 2010
Externally publishedYes

Keywords

  • Bayes' rule
  • LPR
  • Plate localization

ASJC Scopus subject areas

  • Software
  • Hardware and Architecture
  • Computer Vision and Pattern Recognition
  • Computer Science Applications

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