On-Line Video Recognition and Counting of Harmful Insects

Ikhlef Bechar, S. Moisan, M. Thonnat, F. Brémond
{"title":"On-Line Video Recognition and Counting of Harmful Insects","authors":"Ikhlef Bechar, S. Moisan, M. Thonnat, F. Brémond","doi":"10.1109/ICPR.2010.989","DOIUrl":null,"url":null,"abstract":"This article is concerned with on-line counting of harmful insects of certain species in videos in the framework of in situ video-surveillance that aims at the early detection of prominent pest attacks in greenhouse crops. The video-processing challenges that need to be coped with concern mainly the low spatial resolution and color contrast of the objects of interest in the videos, the outdoor issues and the video-processing which needs to be done in quasi-real time. Thus, we propose an approach which makes use of a pattern recognition algorithm to extract the locations of the harmful insects of interest in a video, which we combine with some video-processing algorithms in order to achieve an on-line video-surveillance solution. The system has been validated off-line on the whiteflie species (one potential harmful insect) and has shown acceptable performance in terms of accuracy versus computational time.","PeriodicalId":309591,"journal":{"name":"2010 20th International Conference on Pattern Recognition","volume":"97 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-08-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"22","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2010 20th International Conference on Pattern Recognition","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICPR.2010.989","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 22

Abstract

This article is concerned with on-line counting of harmful insects of certain species in videos in the framework of in situ video-surveillance that aims at the early detection of prominent pest attacks in greenhouse crops. The video-processing challenges that need to be coped with concern mainly the low spatial resolution and color contrast of the objects of interest in the videos, the outdoor issues and the video-processing which needs to be done in quasi-real time. Thus, we propose an approach which makes use of a pattern recognition algorithm to extract the locations of the harmful insects of interest in a video, which we combine with some video-processing algorithms in order to achieve an on-line video-surveillance solution. The system has been validated off-line on the whiteflie species (one potential harmful insect) and has shown acceptable performance in terms of accuracy versus computational time.
有害昆虫的在线视频识别和计数
本文介绍了在现场视频监控框架下,利用视频对某些物种的有害昆虫进行在线计数,以期及早发现温室作物的主要害虫。视频处理面临的挑战主要涉及视频中感兴趣对象的低空间分辨率和低色彩对比度、户外问题以及需要准实时进行的视频处理。因此,我们提出了一种利用模式识别算法提取视频中感兴趣的有害昆虫位置的方法,并将其与一些视频处理算法相结合,以实现在线视频监控解决方案。该系统已在白蝇物种(一种潜在的有害昆虫)上进行了离线验证,并在准确性和计算时间方面显示出可接受的性能。
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 求助全文
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:481959085
Book学术官方微信