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Title: | Weed and himayaritic of leaf detection system with I.P |
Authors: | Chaya, S Tanki, Saim (13ET60) Malik, Ajmal (14ET28) Khan, Junaid (14ET24) Khan, Aziz (13ET22) |
Keywords: | Project Report - EXTC |
Issue Date: | May-2019 |
Publisher: | AIKTC |
Series/Report no.: | PE0494; |
Abstract: | India, thecountrywherethemainsourceofincomeisfromagriculture. Farmersgrowavarietyofcropsbasedontheirrequirement.Sincetheplants su er fromthedisease,theproductionofcropdecreasesduetoinfections caused byseveraltypesofdiseasesonitsleaf,fruit,andstem.Leafdiseases are mainlycausedbybacteria,fungi,virusetc.Diseasesareoftendi cult to control.Diagnosisofthediseaseshouldbedoneaccuratelyandproper actions shouldbetakenattheappropriatetime.ImageProcessingisthe trending techniqueindetectionandclassi cationofplantleafdisease.This workdescribeshowtoautomaticallydetectleafdiseases.Thegivensystem will provideafast,spontaneous,preciseandveryeconomicalmethodin detecting andclassifyingleafdiseases.Thispaperisenvisionedtoassistin the detectingandclassifyingleafdiseasesusingMulticlassSVMclassi cation technique.First,thea ectedregionisdiscoveredusingsegmentationbyK- means clustering,thenfeatures(colorandtexture)areextracted.Lastly, classi cation techniqueisappliedindetectingthetypeofleafdisease. Keywords: Image Processing,Leafdiseasesdetection,K-meansclustering, featureextraction,MulticlassSVMClassi cation. |
Description: | Submitted in partial fulfillment of the requirements for the degree of Bachelor of Engineering 2019 |
URI: | http://www.aiktcdspace.org:8080/jspui/handle/123456789/3046 |
Appears in Collections: | EXTC Engineering - Project Reports |
Files in This Item:
File | Description | Size | Format | |
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GRP13-WEED.pdf | 1.73 MB | Adobe PDF | View/Open |
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