Fast License Plate Recognition Method Based on Competitive Neural Network

DOI

10.2991/cimns-18.2018.26How to use a DOI?

Keywords

License plate recognition; neural network; character detection)

Abstract

Vehicle license plate recognition is an important part of Intelligent Transportation Network. Generally speaking, the traditional LPR mainly consists of three parts: location, segmentation and recognition. Recognition is the most important part of LPR and the effect of recognition is closely related to the result of location segmentation. The accuracy of recognition is the most important index to test the effect of recognition. This paper introduces the recognition method of license plate characters by competitive neural network, and discusses a fast recognition method of the number and letter of vehicle license plate under natural background by using an improved competitive neural network. The results show that the character recognition rate of the images taken under the natural landscape is 91.3%.

Copyright

© 2018, 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  - Jinxing Qian
AU  - Bo Qu
PY  - 2018/11
DA  - 2018/11
TI  - Fast License Plate Recognition Method Based on Competitive Neural Network
BT  - Proceedings of the 2018 3rd International Conference on Communications, Information Management and Network Security (CIMNS 2018)
PB  - Atlantis Press
SP  - 114
EP  - 117
SN  - 2352-538X
UR  - https://doi.org/10.2991/cimns-18.2018.26
DO  - 10.2991/cimns-18.2018.26
ID  - Qian2018/11
ER  -