B. D. D. Nayomi, Ipshitha Charles, S. Krishna, Sandip Swarnakar
{"title":"IDENTIFYING THE ATTACKS ON GROWING PLANTS BASED ON IMAGE PROCESSING","authors":"B. D. D. Nayomi, Ipshitha Charles, S. Krishna, Sandip Swarnakar","doi":"10.57061/ijcict.v11i3.1","DOIUrl":null,"url":null,"abstract":"Image processing is a diverging area where researches and advancements are taking a geometrical progress in the agricultural field. Various researches are going on vigorously in plant disease detection. Identification of plant diseases can not only maximize the yield production but also can be supportive for varied types of agricultural practices. Disease classification on plant is very critical for supportable agriculture. It is very difficult to monitor or treat the plant diseases manually. It requires huge amount of work, and also\nneed the excessive processing time, therefore image processing is used for the detection of plant diseases. Plant disease classification involves the steps like Load image, preprocessing, segmentation, feature extraction, svmClassifer. Detecting disease may be a key to stop agricultural losses. The aim of this project is to develop a software system answer that mechanically find and classify disease.","PeriodicalId":329291,"journal":{"name":"International Journal of Computing, Intelligent and Communication Technology","volume":"26 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Computing, Intelligent and Communication Technology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.57061/ijcict.v11i3.1","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Image processing is a diverging area where researches and advancements are taking a geometrical progress in the agricultural field. Various researches are going on vigorously in plant disease detection. Identification of plant diseases can not only maximize the yield production but also can be supportive for varied types of agricultural practices. Disease classification on plant is very critical for supportable agriculture. It is very difficult to monitor or treat the plant diseases manually. It requires huge amount of work, and also
need the excessive processing time, therefore image processing is used for the detection of plant diseases. Plant disease classification involves the steps like Load image, preprocessing, segmentation, feature extraction, svmClassifer. Detecting disease may be a key to stop agricultural losses. The aim of this project is to develop a software system answer that mechanically find and classify disease.