License plate detection using local structure patterns

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

doi:10.1109/AVSS.2010.48

License plate detection using local structure patterns

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

School of Electrical Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

25 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 language	English
Title of host publication	Proceedings - IEEE International Conference on Advanced Video and Signal Based Surveillance, AVSS 2010
Publisher	IEEE Computer Society
Pages	574-579
Number of pages	6
ISBN (Print)	9780769542645
DOIs	https://doi.org/10.1109/AVSS.2010.48
Publication status	Published - 2010
Event	2010 7th IEEE International Conference on Advanced Video and Signal Based Surveillance, AVSS 2010 - Boston, MA, United States Duration: 2010 Aug 29 → 2010 Sept 1

Publication series

Name	Proceedings - IEEE International Conference on Advanced Video and Signal Based Surveillance, AVSS 2010

Conference

Conference	2010 7th IEEE International Conference on Advanced Video and Signal Based Surveillance, AVSS 2010
Country/Territory	United States
City	Boston, MA
Period	10/8/29 → 10/9/1

ASJC Scopus subject areas

Computer Networks and Communications
Signal Processing

Access to Document

10.1109/AVSS.2010.48

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). Article 5597079 (Proceedings - IEEE International Conference on Advanced Video and Signal Based Surveillance, AVSS 2010). IEEE Computer Society. https://doi.org/10.1109/AVSS.2010.48

License plate detection using local structure patterns. / Lee, Younghyun; Song, Taeyup; Ku, Bonhwa et al.
Proceedings - IEEE International Conference on Advanced Video and Signal Based Surveillance, AVSS 2010. IEEE Computer Society, 2010. p. 574-579 5597079 (Proceedings - IEEE International Conference on Advanced Video and Signal Based Surveillance, AVSS 2010).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Lee, Y, Song, T, Ku, B, Jeon, S, Han, DK & Ko, H 2010, License plate detection using local structure patterns. in Proceedings - IEEE International Conference on Advanced Video and Signal Based Surveillance, AVSS 2010., 5597079, Proceedings - IEEE International Conference on Advanced Video and Signal Based Surveillance, AVSS 2010, IEEE Computer Society, pp. 574-579, 2010 7th IEEE International Conference on Advanced Video and Signal Based Surveillance, AVSS 2010, Boston, MA, United States, 10/8/29. https://doi.org/10.1109/AVSS.2010.48

Lee Y, Song T, Ku B, Jeon S, Han DK, Ko H. License plate detection using local structure patterns. In Proceedings - IEEE International Conference on Advanced Video and Signal Based Surveillance, AVSS 2010. IEEE Computer Society. 2010. p. 574-579. 5597079. (Proceedings - IEEE International Conference on Advanced Video and Signal Based Surveillance, AVSS 2010). doi: 10.1109/AVSS.2010.48

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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.",

author = "Younghyun Lee and Taeyup Song and Bonhwa Ku and Seoungseon Jeon and Han, {David K.} and Hanseok Ko",

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AB - 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.

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License plate detection using local structure patterns

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