A hierarchical license plate recognition system using supervised K-means and support vector machine

Wei Chen Liu, Cheng Hung Lin

Research output: Chapter in Book/Report/Conference proceedingConference contribution

6 Citations (Scopus)

Abstract

In recent years, the use of license plate recognition technology in traffic monitor has attracted a lot of attention because it can be used in a smart city to do criminal investigation and traffic detection. License plate recognition technology has been widely used in parking lot management systems which has fixed shooting angle and lighting environments. The license plate recognition used in traffic monitor will encounter difficulties in character recognition due to factors such as shooting angle, vehicle speed and environment light and shadow. Aiming at the blurred and skewed character images caused by the above factors, this paper presents a hierarchical architecture combining supervised K-means and support vector machine. The supervised K-means is used to classify characters into subgroups. The characters of subgroups can be further classified by support vector machine. The advantage of the proposed approach is to reduce the classes of characters in each subgroup to further reduce the number of SVMs and their complexity, and thus improve the accuracy of character recognition. Experimental results show that our proposed hierarchical architecture achieves an accuracy of 98.89% in character recognition. Compared with the license plate recognition technology using SVM alone, we get a 3.6% improvement in recognition rate.

Original languageEnglish
Title of host publicationProceedings of the 2017 IEEE International Conference on Applied System Innovation
Subtitle of host publicationApplied System Innovation for Modern Technology, ICASI 2017
EditorsTeen-Hang Meen, Artde Donald Kin-Tak Lam, Stephen D. Prior
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1622-1625
Number of pages4
ISBN (Electronic)9781509048977
DOIs
Publication statusPublished - 2017 Jul 21
Event2017 IEEE International Conference on Applied System Innovation, ICASI 2017 - Sapporo, Japan
Duration: 2017 May 132017 May 17

Publication series

NameProceedings of the 2017 IEEE International Conference on Applied System Innovation: Applied System Innovation for Modern Technology, ICASI 2017

Other

Other2017 IEEE International Conference on Applied System Innovation, ICASI 2017
CountryJapan
CitySapporo
Period17/5/1317/5/17

Keywords

  • Character recognition
  • K-means
  • License plate recognition
  • Support vector machine

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Computer Science Applications
  • Hardware and Architecture
  • Safety, Risk, Reliability and Quality
  • Mechanical Engineering
  • Media Technology
  • Health Informatics
  • Instrumentation

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  • Cite this

    Liu, W. C., & Lin, C. H. (2017). A hierarchical license plate recognition system using supervised K-means and support vector machine. In T-H. Meen, A. D. K-T. Lam, & S. D. Prior (Eds.), Proceedings of the 2017 IEEE International Conference on Applied System Innovation: Applied System Innovation for Modern Technology, ICASI 2017 (pp. 1622-1625). [7988244] (Proceedings of the 2017 IEEE International Conference on Applied System Innovation: Applied System Innovation for Modern Technology, ICASI 2017). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICASI.2017.7988244