License plate detection using local structure patterns

Younghyun Lee, Taeyup Song, Bonhwa Ku, Seoungseon Jeon, David K. Han, Hanseok Ko

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

20 Citations (Scopus)

Abstract

We address the problem of license plate detection in video surveillance systems. The Adaboost based approach, known for relative ease of implementation, makes use of discriminative features such as edges or Haar-like features. In this paper, we propose a novel detection algorithm based on local structure patterns for license plate detection. The proposed algorithm includes post-processing methods to reduce false positive rate using positional and color information of license plates. Experimental results demonstrate effectiveness of the proposed method compared to both the edge and Haar-like feature based methods.

Original languageEnglish
Title of host publicationProceedings - IEEE International Conference on Advanced Video and Signal Based Surveillance, AVSS 2010
Pages574-579
Number of pages6
DOIs
Publication statusPublished - 2010 Nov 24
Event2010 7th IEEE International Conference on Advanced Video and Signal Based, AVSS 2010 - Boston, MA, United States
Duration: 2010 Aug 292010 Sep 1

Other

Other2010 7th IEEE International Conference on Advanced Video and Signal Based, AVSS 2010
CountryUnited States
CityBoston, MA
Period10/8/2910/9/1

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ASJC Scopus subject areas

  • Computer Networks and Communications
  • Signal Processing

Cite this

Lee, Y., Song, T., Ku, B., Jeon, S., Han, D. K., & Ko, H. (2010). License plate detection using local structure patterns. In Proceedings - IEEE International Conference on Advanced Video and Signal Based Surveillance, AVSS 2010 (pp. 574-579). [5597079] https://doi.org/10.1109/AVSS.2010.48