{"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.