Proceedings of the First International Conference on Information Science and Electronic Technology

Hybrid Method for License Plate Detection from Natural Scene Images

Authors
Boya Niu, Linlin Huang, Jian Hu
Corresponding Author
Boya Niu
Available Online March 2015.
DOI
10.2991/iset-15.2015.9How to use a DOI?
Keywords
License plate detection, Color pairs, Mathematical morphology, HOG feature, SVM
Abstract

License plate detection is a key part in vehicle license plate recognition system. In this paper, we present a hybrid method for license plate detection from natural scene images for the all-day traffic surveillance environment. The proposed method includes two stages: rough detection and accurate detection. Coarse detection stage based on color edge and morphology can help finding the region of interest quickly. Accurate detection stage based on HOG and SVM accurately detect the vehicle license plate. The effectiveness of the proposed method has been proven by the experimental results on a large database of images.

Copyright
© 2015, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Download article (PDF)

Volume Title
Proceedings of the First International Conference on Information Science and Electronic Technology
Series
Advances in Computer Science Research
Publication Date
March 2015
ISBN
978-94-62520-50-9
ISSN
2352-538X
DOI
10.2991/iset-15.2015.9How to use a DOI?
Copyright
© 2015, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - CONF
AU  - Boya Niu
AU  - Linlin Huang
AU  - Jian Hu
PY  - 2015/03
DA  - 2015/03
TI  - Hybrid Method for License Plate Detection from Natural Scene Images
BT  - Proceedings of the First International Conference on Information Science and Electronic Technology
PB  - Atlantis Press
SP  - 32
EP  - 36
SN  - 2352-538X
UR  - https://doi.org/10.2991/iset-15.2015.9
DO  - 10.2991/iset-15.2015.9
ID  - Niu2015/03
ER  -