An algorithm for accuracy enhancement of license plate recognition

Lihong Zheng, Xiangjian He, Bijan Samali, Laurence T. Yang

Research output: Journal PublicationArticlepeer-review

42 Citations (Scopus)

Abstract

This paper presents an algorithm for extraction (detection) and recognition of license plates in traffic video datasets. For license plate detection, we introduce a method that applies both global edge features and local Haar-like features to construct a cascaded classifier consisting of 6 layers with 160 features. The characters on a license plate image are extracted by a method based on an improved blob detection algorithm for removal of unwanted areas. For license plate recognition (i.e., character recognition), an open source OCR is modified and used. Our proposed system is robust under poor illumination conditions and for moving vehicles. Our overall system is efficient and can be applied in real-time applications. Experimental results are demonstrated using a traffic video.

Original languageEnglish
Pages (from-to)245-255
Number of pages11
JournalJournal of Computer and System Sciences
Volume79
Issue number2
DOIs
Publication statusPublished - Mar 2013
Externally publishedYes

Keywords

  • Blob detection algorithm
  • Haar-like features
  • Image segmentation
  • License plate detection
  • OCR
  • Statistical features

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Networks and Communications
  • Computational Theory and Mathematics
  • Applied Mathematics

Fingerprint

Dive into the research topics of 'An algorithm for accuracy enhancement of license plate recognition'. Together they form a unique fingerprint.

Cite this