Proceedings of the 2017 5th International Conference on Machinery, Materials and Computing Technology (ICMMCT 2017)

Research on license plate recognition based on video image processing

Authors
Gang Shen
Corresponding Author
Gang Shen
Available Online April 2017.
DOI
10.2991/icmmct-17.2017.220How to use a DOI?
Keywords
License plate location; license plate character segmentation; license plate recognition;
Abstract

This paper researched the license plate recognition system based on video image processing. In the pretreatment process of license plate recognition, the paper uses image gray, gray stretch and a series of processing methods of image processing to process the license plate. In the license plate location, this paper introduces a new method which is based on the mathematical morphology and then uses the image binaryzation to locate the license plate location algorithm. This paper used MATLAB as a platform to achieve the design and implementation of the license plate recognition. Experiments show that the method proposed in this paper is effective and has practical value.

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 2017 5th International Conference on Machinery, Materials and Computing Technology (ICMMCT 2017)
Series
Advances in Engineering Research
Publication Date
April 2017
ISBN
978-94-6252-318-0
ISSN
2352-5401
DOI
10.2991/icmmct-17.2017.220How 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  - Gang Shen
PY  - 2017/04
DA  - 2017/04
TI  - Research on license plate recognition based on video image processing
BT  - Proceedings of the 2017 5th International Conference on Machinery, Materials and Computing Technology (ICMMCT 2017)
PB  - Atlantis Press
SP  - 1105
EP  - 1110
SN  - 2352-5401
UR  - https://doi.org/10.2991/icmmct-17.2017.220
DO  - 10.2991/icmmct-17.2017.220
ID  - Shen2017/04
ER  -