Proceedings of the 2016 4th International Conference on Machinery, Materials and Information Technology Applications

Using Artificial Bees Colony Algorithm for License Plate Recognition

Authors
Weiyu Yu, Dan Hu, Chuyi Li
Corresponding Author
Weiyu Yu
Available Online January 2017.
DOI
10.2991/icmmita-16.2016.10How to use a DOI?
Keywords
vehicle plate recognition; artificial bee colony algorithm; image preprocessing
Abstract

In this paper, a new vehicle plate recognition method is proposed using the artificial bee colony algorithm. This method can be implemented in entrance admission, security, airport or harbor cargo control, traffic control. Artificial bee colony algorithm was first introduced by Dervis Karaboga in 2005 for solving numerical optimization problems. ABC algorithm has achieved better results on the optimization problems. We use ABCA on image transformation, enhancement, denoise and BP network. Experimental results showed proposed method is effective and effect.

Copyright
© 2017, 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/).

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Volume Title
Proceedings of the 2016 4th International Conference on Machinery, Materials and Information Technology Applications
Series
Advances in Computer Science Research
Publication Date
January 2017
ISBN
10.2991/icmmita-16.2016.10
ISSN
2352-538X
DOI
10.2991/icmmita-16.2016.10How to use a DOI?
Copyright
© 2017, 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  - Weiyu Yu
AU  - Dan Hu
AU  - Chuyi Li
PY  - 2017/01
DA  - 2017/01
TI  - Using Artificial Bees Colony Algorithm for License Plate Recognition
BT  - Proceedings of the 2016 4th International Conference on Machinery, Materials and Information Technology Applications
PB  - Atlantis Press
SP  - 51
EP  - 55
SN  - 2352-538X
UR  - https://doi.org/10.2991/icmmita-16.2016.10
DO  - 10.2991/icmmita-16.2016.10
ID  - Yu2017/01
ER  -