Recognition of Vehicle License Plate Based on Hopfield Artificial Neural Network

被引：0

作者：

Lan, Tian-Syung ^{[1
,2
]}

Li, Jiawei ^{[1
]}

Dai, Xuan-Jun ^{[1
]}

Chen, Ho-Sheng ^{[3
]}

Liu, Ruiming ^{[4
]}

机构：

[1] Guilin Univ Technol, Coll Mech & Control Engn, Guilin 541004, Guangxi, Peoples R China

[2] Yu Da Univ Sci & Technol, Dept Informat Management, Miaoli 36143, Taiwan

[3] Guangdong Univ Petrochem Technol, Coll Mech & Elect Engn, Maoming 525000, Guangdong, Peoples R China

[4] Jiangsu Ocean Univ, Lianyungang 222005, Jiangsu, Peoples R China

来源：

SENSORS AND MATERIALS | 2021年 / 33卷 / 11期

关键词：

Hopfield; general license plate number recognition; image recognition;

D O I：

10.18494/SAM.2021.3518

中图分类号：

TH7 [仪器、仪表];

学科分类号：

0804 ; 080401 ; 081102 ;

摘要：

Vehicle license plate recognition has become widely used to control and efficiently manage transportation systems. The increasing number of vehicles and worsening congestion on the road make the accuracy of the traditional recognition system low. Thus, introducing a neural network in license plate recognition has been paid considerable attention. In this paper, we aim to enhance recognition accuracy by using the Hopfield artificial neural network (ANN). Test results showed that the recognition method based on the Hopfield ANN is found to be efficient and accurate.

引用

页码：3983 / 3990

页数：8

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