Improvement of the Vehicle License Plate Recognition System in the Environment of Rain and Fog

DOI

10.2991/icitmi-15.2015.112How to use a DOI?

Keywords

License Plate Recognition; Gamma Correction; Double Color Space; Neural Network Recognition; Adaptive Fusion Algorithm

Abstract

License Plate Recognition (LPR) is one of the key technologies of the intelligence of communication management. A certain amount of difficulties to license plate recognition are caused by the environment of rain and fog. License plate recognition system for this kind of environment is studied in this paper, based on the theory of digital image processing, computer vision and pattern recognition technology. In order to improve the ability to identify the license plate, Gamma correction algorithm and the denoising algorithm of color image are added to license plate locating method based on color. In the pre-processing of the segmentation method based on connected area detection, a kind of double color space binarization method is proposed by the article. Finally a kind of adaptive fusion algorithm based on BP, RBF, GRNN neural network is proposed to finish the recognition for license plate character. Experiment shows that the method adopted by this system applied in the bad environment of rain and fog achieves good recognition effect.

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/).

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TY  - CONF
AU  - Zhun Wang
AU  - Zhenyu Liu
PY  - 2015/10
DA  - 2015/10
TI  - Improvement of the Vehicle License Plate Recognition System in the Environment of Rain and Fog
BT  - Proceedings of the 4th International Conference on Information Technology and Management Innovation
PB  - Atlantis Press
SP  - 670
EP  - 679
SN  - 2352-538X
UR  - https://doi.org/10.2991/icitmi-15.2015.112
DO  - 10.2991/icitmi-15.2015.112
ID  - Wang2015/10
ER  -