图像特征提取在基于农业发展的交通道路中心线识别中的应用

Shuang Shi
{"title":"图像特征提取在基于农业发展的交通道路中心线识别中的应用","authors":"Shuang Shi","doi":"10.5912/jcb1232","DOIUrl":null,"url":null,"abstract":"In order to improve the recognition efficiency of traffic road centerline recognition method, a traffic road centerline recognition method based on speech recognition technology and image feature extraction is designed. Firstly, the remote sensing image is preprocessed, and then the road knowledge base of traffic road image is established, which mainly includes four parts: road feature analysis, building road extraction knowledge base, high-resolution remote sensing image road rule set and traffic road image classification. On this basis, the image is classified, and finally the road midline feature points are extracted by proportion space theory to realize the final intersection Central line identification of access road. The experimental results show that the recognition time of the proposed method is less than that of the traditional method, and the recognition accuracy is high, which has a certain practical significance.","PeriodicalId":88541,"journal":{"name":"Journal of commercial biotechnology","volume":" ","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2022-08-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Application of Image Feature Extraction in Traffic Road Centerline Recognition based on agricultural development\",\"authors\":\"Shuang Shi\",\"doi\":\"10.5912/jcb1232\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In order to improve the recognition efficiency of traffic road centerline recognition method, a traffic road centerline recognition method based on speech recognition technology and image feature extraction is designed. Firstly, the remote sensing image is preprocessed, and then the road knowledge base of traffic road image is established, which mainly includes four parts: road feature analysis, building road extraction knowledge base, high-resolution remote sensing image road rule set and traffic road image classification. On this basis, the image is classified, and finally the road midline feature points are extracted by proportion space theory to realize the final intersection Central line identification of access road. The experimental results show that the recognition time of the proposed method is less than that of the traditional method, and the recognition accuracy is high, which has a certain practical significance.\",\"PeriodicalId\":88541,\"journal\":{\"name\":\"Journal of commercial biotechnology\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-08-25\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of commercial biotechnology\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.5912/jcb1232\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of commercial biotechnology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.5912/jcb1232","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

为了提高交通道路中线识别方法的识别效率,设计了一种基于语音识别技术和图像特征提取的交通道路中线辨识方法。首先对遥感图像进行预处理,然后建立交通道路图像的道路知识库,主要包括四个部分:道路特征分析、构建道路提取知识库、高分辨率遥感图像道路规则集和交通道路图像分类。在此基础上,对图像进行分类,最后利用比例空间理论提取道路中线特征点,实现最终的入口道路交叉口中线识别。实验结果表明,该方法比传统方法识别时间短,识别精度高,具有一定的现实意义。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Application of Image Feature Extraction in Traffic Road Centerline Recognition based on agricultural development
In order to improve the recognition efficiency of traffic road centerline recognition method, a traffic road centerline recognition method based on speech recognition technology and image feature extraction is designed. Firstly, the remote sensing image is preprocessed, and then the road knowledge base of traffic road image is established, which mainly includes four parts: road feature analysis, building road extraction knowledge base, high-resolution remote sensing image road rule set and traffic road image classification. On this basis, the image is classified, and finally the road midline feature points are extracted by proportion space theory to realize the final intersection Central line identification of access road. The experimental results show that the recognition time of the proposed method is less than that of the traditional method, and the recognition accuracy is high, which has a certain practical significance.
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
CiteScore
1.20
自引率
0.00%
发文量
0
期刊最新文献
Unpacking the association between attachment insecurity and PTSD symptoms: The mediating role of coping strategies. Images: Polysomnographic artifact in a patient with Tourette syndrome. Investigating the impact of cross-cultural adaptability on the academic and social experiences of international students in bioethics education. Exploring the potential of using Marxist network management to address the challenges of bioethics education in higher medical colleges. Investigating the effectiveness of bio-feedback techniques in improving English vocabulary learning in ESL learners.
×
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
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 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 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1