research-article

Automatic number plate detection for Korean vehicles

Authors:

ICIS '09: Proceedings of the 2nd International Conference on Interaction Sciences: Information Technology, Culture and Human

Pages 1191 - 1195

https://doi.org/10.1145/1655925.1656142

Published: 24 November 2009 Publication History

Get Access

Abstract

We consider the task of detection of Korean vehicle number plates (also named license plates or registration plates in other countries). A system for number plate detection must cope with wide variations in the appearance of the plates. Few yeas ago, Korea government permits the new types of license plates with wide width as same as foreign country. It occurred that the new license plates detection algorithm was needed. We have developed a system that makes precise decision rules for detecting plate area using priori-knowledge about various plate types. According to the lighting condition, seed processing as adaptive Sobel edge is very important. In some cases, plate candidate areas are not selected. And then, we retry to Sobel edge detection with strong threshold value. Final detection results have shown that proposed detection algorithm is very useful.

References

[1]

Young Sung Soh, Byung Tae Chun and Ho Sub Yoon, "Design of real time vehicle identification system," Design of real time vehicle identification system," IEEE International Conference on Systems, Man, and Cybernetics, Volume 3, Page(s):2147--2152, Oct. 1994.

Google Scholar

[2]

T. Wagner, P. Plankensteiner and N. Bauer, Parked Cars Licence Plate Detection System, Patent DE19650756, 1997.

Google Scholar

[3]

L. Toledo, and F. Cuevas, "Binary threshold algorithm for license plate character segmentation," Proceedings of the International Society for Optical Engineering, vol.6046, pp. 60461H, 2006.

Google Scholar

[4]

F. Yang, Z. Ma, and M. Xie, "A novel approach for license plate character segmentation," IEEE Conference on Industrial Electronics and Applications, pp. 4025835, 2006.

Google Scholar

[5]

A. Vahid, and A. Alireza, "A fast algorithm for license plate detection," 9th International Conference on Visual Information Systems, vol.4781, LNCS, pp.468--477, 2007.

Digital Library

Google Scholar

[6]

T. Sirthinaphong, and K. Chammonthai, "The recognition of car license plate for automatic parking system," Processing of the Fifth International Symposium on Signal Processing and its Applications, vol.1, pp.455--457, 1999.

Crossref

Google Scholar

[7]

M. H. Terbrugge, J. H. Stevens, and G. Nijhuis, "License plate recognition using DTCNNS," Proceedings of the IEEE International Workshop on Cellular Neural Networks and their Applications, pp.212--217, 1998.

Google Scholar

[8]

Z. Rodolfo, and R. Stefano, "Vector quantization for license plate location and image coding," IEEE Transaction on Industrial Electronics, vol.47, pp.159--167, 2000.

Crossref

Google Scholar

[9]

Leonard G. C. Hamey, and Colin Priest, "Automatic Number Plate Recognition for Australian Conditions," Digital Image Computing: Techniques and Applications, Page(s):14--14, 2005.

Digital Library

Google Scholar

[10]

Bei CHEN, Wenlun CAO, and Hongcai ZHANG, "An Efficient Algorithm on Vehicle License Plate Location," Proceedings of the IEEE International Conference on Automation and Logistics Qingdao, China, pp. 1386--1389, September 2008.

Google Scholar

Cited By

View all

Islam TMehedi Hasan Abid D(2022)Automatic Vehicle Bangla License Plate Detection and RecognitionSmart Data Intelligence10.1007/978-981-19-3311-0_44(523-534)Online publication date: 18-Aug-2022
https://doi.org/10.1007/978-981-19-3311-0_44

Index Terms

Automatic number plate detection for Korean vehicles
1. Computing methodologies
  1. Artificial intelligence
    1. Computer vision
      1. Computer vision problems
      2. Computer vision tasks
        Scene understanding
  2. Computer graphics
    1. Image manipulation

Recommendations

A Novel Method for Indian Vehicle Registration Number Plate Detection and Recognition using Image Processing Techniques
Abstract
Number Plate recognition, also called License Plate realization or recognition using image processing methods is a potential research area in smart cities and Internet of Things. Many of the existing automated number plate recognition systems work ...
Synthetic image generation for training deep learning-based automated license plate recognition systems on the Brazilian Mercosur standard
Abstract
License plates are the primary source of vehicle identification data used in a wide range of applications including law enforcement, electronic tolling, and access control amongst others. License plate detection (LPD) is a critical process in ...
License plate detection for multi-national vehicles: An illumination invariant approach in multi-lane environment
Highlights
- License plate detection for multi-national vehicles in a multi-lane scenario.
- ...
Abstract
Only a few methods in literature are effective for multi-national license plate detection in a multi-lane scenario. These methods are prone to illumination variance, complex background and weak-edged license plates. In this paper, we ...

Comments

Please enable JavaScript to view thecomments powered by Disqus.

Information & Contributors

Information

Published In

ICIS '09: Proceedings of the 2nd International Conference on Interaction Sciences: Information Technology, Culture and Human

November 2009

1479 pages

ISBN:9781605587103

DOI:10.1145/1655925

Conference Chairs:
Sungwon Sohn
ETRI, Korea
,
Kyhyun Um
Dongguk University, Korea
,
Franz I. S. Ko
Dongguk University, Korea/IBC, UK
,
Kae Dal Kwack
Hanyang University, Korea
,
Jong Hyung Lee
Gumi Electronics & Information Technology Research Institute, Korea
,
Gang Kou
University of Electronic Science and Technology of China, China
,
Kiyoshi Nakamura
Waseda University, Japan
,
ACM Fong
Nanyang Technological University, Singapore
,
Patrick Ma
The Hong Kong Polytechnic University, Hongkong
,
Ling Chen
Zhejiang University, China
,
Soonwook Hwang
KISTI, Korea
,
Kyungeun Cho
Dongguk University, Korea
,
Shigeo Kawata
Utsunomiya University, Japan

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 24 November 2009

Permissions

Request permissions for this article.

Request Permissions

Check for updates

Author Tags

Qualifiers

Research-article

Conference

ICIS '09

Sponsor:

ICIS '09: The 2nd International Conference on Interaction Sciences: Information Technology, Culture and Human

November 24 - 26, 2009

Seoul, Korea

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

1
Total Citations
View Citations
41
Total Downloads

Downloads (Last 12 months)0
Downloads (Last 6 weeks)0

Reflects downloads up to 19 Nov 2024

Other Metrics

View Author Metrics

Citations

Cited By

View all

Islam TMehedi Hasan Abid D(2022)Automatic Vehicle Bangla License Plate Detection and RecognitionSmart Data Intelligence10.1007/978-981-19-3311-0_44(523-534)Online publication date: 18-Aug-2022
https://doi.org/10.1007/978-981-19-3311-0_44

View Options

Login options

Check if you have access through your login credentials or your institution to get full access on this article.

Cited By

Index Terms

Recommendations

A Novel Method for Indian Vehicle Registration Number Plate Detection and Recognition using Image Processing Techniques

Synthetic image generation for training deep learning-based automated license plate recognition systems on the Brazilian Mercosur standard

License plate detection for multi-national vehicles: An illumination invariant approach in multi-lane environment