Design and Implementation of License Plate Recongnition System based on Deep Learning

被引:0
|
作者
Zhang, Bianlian [1 ,2 ]
Liu, Zhaohua [1 ,2 ]
Zhang, Xiaoli [1 ,2 ]
机构
[1] Xian Univ, Shaanxi Key Lab Surface Engn & Remfg, Xian 710065, Peoples R China
[2] Xian Univ, Sch Mechan & Mat Engn, Xian 710065, Shaanxi, Peoples R China
关键词
Neural Networks; Deep learning; License Plate Recognition; Convolutional neural network;
D O I
10.1117/12.2551026
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
This paper is based on the deep learning license plate recognition system, which is a method of deep learning in the recognition of license plates.In the recognition of license plates, improved Convolutional-Neural-Network (CNN) is used to identify the accuracy and speed of recognition. The experimental results show that the application of convolutional neural network in license plate recognition can effectively improve the recognition rate of the license plate in various environments such as pollution, insufficient illumination, etc. This recognition rate is improved by means of a large training character set. The more character forms included in the character set, the higher the recognition rate, the more the license plate character recognition rate can reach 98% or more. In addition, for the trained convolutional neural network, including the license plate extraction and pre-processing recognition speed can also reach less than 30 ms.
引用
收藏
页数:6
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