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

Wei Chen Liu; Cheng Hung Lin

doi:10.1109/ICASI.2017.7988244

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

Wei Chen Liu
, Cheng Hung Lin

Department of Electrical Engineering

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

28 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 language	English
Title of host publication	Proceedings of the 2017 IEEE International Conference on Applied System Innovation
Subtitle of host publication	Applied System Innovation for Modern Technology, ICASI 2017
Editors	Teen-Hang Meen, Artde Donald Kin-Tak Lam, Stephen D. Prior
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	1622-1625
Number of pages	4
ISBN (Electronic)	9781509048977
DOIs	https://doi.org/10.1109/ICASI.2017.7988244
Publication status	Published - 2017 Jul 21
Event	2017 IEEE International Conference on Applied System Innovation, ICASI 2017 - Sapporo, Japan Duration: 2017 May 13 → 2017 May 17

Publication series

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

Other

Other	2017 IEEE International Conference on Applied System Innovation, ICASI 2017
Country/Territory	Japan
City	Sapporo
Period	2017/05/13 → 2017/05/17

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 11 Sustainable Cities and Communities
SDG 16 Peace, Justice and Strong Institutions

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

Access to Document

10.1109/ICASI.2017.7988244

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). Article 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

A hierarchical license plate recognition system using supervised K-means and support vector machine. / Liu, Wei Chen; Lin, Cheng Hung.
Proceedings of the 2017 IEEE International Conference on Applied System Innovation: Applied System Innovation for Modern Technology, ICASI 2017. ed. / Teen-Hang Meen; Artde Donald Kin-Tak Lam; Stephen D. Prior. Institute of Electrical and Electronics Engineers Inc., 2017. p. 1622-1625 7988244 (Proceedings of the 2017 IEEE International Conference on Applied System Innovation: Applied System Innovation for Modern Technology, ICASI 2017).

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

Liu, WC & Lin, CH 2017, A hierarchical license plate recognition system using supervised K-means and support vector machine. in T-H Meen, ADK-T Lam & SD Prior (eds), Proceedings of the 2017 IEEE International Conference on Applied System Innovation: Applied System Innovation for Modern Technology, ICASI 2017., 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., pp. 1622-1625, 2017 IEEE International Conference on Applied System Innovation, ICASI 2017, Sapporo, Japan, 2017/05/13. https://doi.org/10.1109/ICASI.2017.7988244

Liu WC, Lin CH. A hierarchical license plate recognition system using supervised K-means and support vector machine. In Meen TH, Lam ADKT, Prior SD, editors, 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. 2017. p. 1622-1625. 7988244. (Proceedings of the 2017 IEEE International Conference on Applied System Innovation: Applied System Innovation for Modern Technology, ICASI 2017). doi: 10.1109/ICASI.2017.7988244

Liu, Wei Chen ; Lin, Cheng Hung. / A hierarchical license plate recognition system using supervised K-means and support vector machine. Proceedings of the 2017 IEEE International Conference on Applied System Innovation: Applied System Innovation for Modern Technology, ICASI 2017. editor / Teen-Hang Meen ; Artde Donald Kin-Tak Lam ; Stephen D. Prior. Institute of Electrical and Electronics Engineers Inc., 2017. pp. 1622-1625 (Proceedings of the 2017 IEEE International Conference on Applied System Innovation: Applied System Innovation for Modern Technology, ICASI 2017).

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AB - 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.

KW - Character recognition

KW - K-means

KW - License plate recognition

KW - Support vector machine

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

Abstract

Publication series

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UN SDGs

Keywords

ASJC Scopus subject areas

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