基于人工神经网络的车牌号码分割识别方法

C. Bal, Auwal S. Yunusa, A. M. Abdu, A. Abdullahi, Aliyu L. Musa, Aliyu M. Sani
{"title":"基于人工神经网络的车牌号码分割识别方法","authors":"C. Bal, Auwal S. Yunusa, A. M. Abdu, A. Abdullahi, Aliyu L. Musa, Aliyu M. Sani","doi":"10.1109/iisec54230.2021.9672356","DOIUrl":null,"url":null,"abstract":"This article presents a license plate number recognition system for moving vehicles for Turkish license plates. The proposed system is designed to read information of vehicle plate numbers automatically from digital images for many purposes; such as over-speed control, parking areas, traffic control, and top governmental agencies, etc. The proposed system mainly consists of two stages: the first stages are the recognition process which consists of vehicle detection from license plate number, localizing and plate position estimation, segmentation of words and numbers, and license plate recognition stage. The second one is the use of the neural network; three different types of networks were used. (pattern net, perceptron, and multi-layer neural network). simulation result indicated that pattern net has a very good performance in recognizing the license plate image compared to the other two types of networks. Also, has the advantage of less training time compared to other types of neural networks.","PeriodicalId":344273,"journal":{"name":"2021 2nd International Informatics and Software Engineering Conference (IISEC)","volume":"32 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Plate Number Recognition Using Segmented Method With Artificial Neural Network\",\"authors\":\"C. Bal, Auwal S. Yunusa, A. M. Abdu, A. Abdullahi, Aliyu L. Musa, Aliyu M. Sani\",\"doi\":\"10.1109/iisec54230.2021.9672356\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This article presents a license plate number recognition system for moving vehicles for Turkish license plates. The proposed system is designed to read information of vehicle plate numbers automatically from digital images for many purposes; such as over-speed control, parking areas, traffic control, and top governmental agencies, etc. The proposed system mainly consists of two stages: the first stages are the recognition process which consists of vehicle detection from license plate number, localizing and plate position estimation, segmentation of words and numbers, and license plate recognition stage. The second one is the use of the neural network; three different types of networks were used. (pattern net, perceptron, and multi-layer neural network). simulation result indicated that pattern net has a very good performance in recognizing the license plate image compared to the other two types of networks. Also, has the advantage of less training time compared to other types of neural networks.\",\"PeriodicalId\":344273,\"journal\":{\"name\":\"2021 2nd International Informatics and Software Engineering Conference (IISEC)\",\"volume\":\"32 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-12-16\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2021 2nd International Informatics and Software Engineering Conference (IISEC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/iisec54230.2021.9672356\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 2nd International Informatics and Software Engineering Conference (IISEC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/iisec54230.2021.9672356","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

本文介绍了一种用于土耳其车牌移动车辆的车牌号码识别系统。该系统能够从数字图像中自动读取车牌号码信息,具有多种用途;如超速管制、停车区、交通管制、政府高层机构等。该系统主要分为两个阶段:第一阶段是车牌识别过程,包括车牌号码检测、车牌定位和位置估计、单词和数字分割以及车牌识别阶段;第二种是神经网络的应用;使用了三种不同类型的网络。(模式网,感知器和多层神经网络)。仿真结果表明,与其他两种类型的网络相比,模式网络在车牌图像识别方面具有很好的性能。同时,与其他类型的神经网络相比,具有训练时间更短的优点。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Plate Number Recognition Using Segmented Method With Artificial Neural Network
This article presents a license plate number recognition system for moving vehicles for Turkish license plates. The proposed system is designed to read information of vehicle plate numbers automatically from digital images for many purposes; such as over-speed control, parking areas, traffic control, and top governmental agencies, etc. The proposed system mainly consists of two stages: the first stages are the recognition process which consists of vehicle detection from license plate number, localizing and plate position estimation, segmentation of words and numbers, and license plate recognition stage. The second one is the use of the neural network; three different types of networks were used. (pattern net, perceptron, and multi-layer neural network). simulation result indicated that pattern net has a very good performance in recognizing the license plate image compared to the other two types of networks. Also, has the advantage of less training time compared to other types of neural networks.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信