Please use this identifier to cite or link to this item: http://localhost:8080/xmlui/handle/123456789/3046
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

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