Disease detection in crops using remote sensing images

Leninisha Shanmugam, A. L. A. Adline, N. Aishwarya, G. Krithika
{"title":"Disease detection in crops using remote sensing images","authors":"Leninisha Shanmugam, A. L. A. Adline, N. Aishwarya, G. Krithika","doi":"10.1109/TIAR.2017.8273696","DOIUrl":null,"url":null,"abstract":"This paper describes an automated diseases detection using remote sensing images. Agriculturists are facing loss due to various crop diseases. It becomes tedious to the cultivators to monitor the crops regularly when the cultivated area is huge (in acres). The most significant part of our research is early detection the disease as soon as it starts spreading on the top layer of the leaves using remote sensing images. This approach has two phases: first phase deals with training of healthy and as well as diseased datasets i.e.) the extraction of threshold values from the image, second phase deals with monitoring of crops and identification of particular disease using canny edge detection algorithm and histogram analysis and also intimate the agriculturists with an early alert message immediately.","PeriodicalId":149469,"journal":{"name":"2017 IEEE Technological Innovations in ICT for Agriculture and Rural Development (TIAR)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-04-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"9","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 IEEE Technological Innovations in ICT for Agriculture and Rural Development (TIAR)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/TIAR.2017.8273696","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 9

Abstract

This paper describes an automated diseases detection using remote sensing images. Agriculturists are facing loss due to various crop diseases. It becomes tedious to the cultivators to monitor the crops regularly when the cultivated area is huge (in acres). The most significant part of our research is early detection the disease as soon as it starts spreading on the top layer of the leaves using remote sensing images. This approach has two phases: first phase deals with training of healthy and as well as diseased datasets i.e.) the extraction of threshold values from the image, second phase deals with monitoring of crops and identification of particular disease using canny edge detection algorithm and histogram analysis and also intimate the agriculturists with an early alert message immediately.
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
利用遥感图像检测作物病害
本文介绍了一种基于遥感图像的疾病自动检测方法。由于各种作物病害,农学家正面临着损失。当耕地面积很大(以亩计)时,对耕种者来说,定期监测收成就变得单调乏味了。我们的研究最重要的部分是利用遥感图像在疾病开始在叶子的顶层传播时及早发现疾病。该方法有两个阶段:第一阶段处理健康和患病数据集的训练,即从图像中提取阈值,第二阶段处理使用精明的边缘检测算法和直方图分析监测作物和识别特定疾病,并立即向农民提供早期警报信息。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Multi-node wireless surveillance system for commercial plantations Design alternatives for end user communication in IoT based system model Vehicle positioning system with accident detection using accelerometer sensor and Android technology Automatic plant monitoring and controlling system over GSM using sensors Forecasting and monitoring maize production using satellite imagery in Rwanda
×
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