Weed and himayaritic of leaf detection system with I.P

Chaya, S; Tanki, Saim (13ET60); Malik, Ajmal (14ET28); Khan, Junaid (14ET24); Khan, Aziz (13ET22)

dc.contributor.author	Chaya, S
dc.contributor.author	Tanki, Saim (13ET60)
dc.contributor.author	Malik, Ajmal (14ET28)
dc.contributor.author	Khan, Junaid (14ET24)
dc.contributor.author	Khan, Aziz (13ET22)
dc.date.accessioned	2019-05-30T05:20:30Z
dc.date.available	2019-05-30T05:20:30Z
dc.date.issued	2019-05
dc.identifier.uri	http://www.aiktcdspace.org:8080/jspui/handle/123456789/3046
dc.description	Submitted in partial fulfillment of the requirements for the degree of Bachelor of Engineering 2019	en_US
dc.description.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.	en_US
dc.language.iso	en	en_US
dc.publisher	AIKTC	en_US
dc.relation.ispartofseries	PE0494;
dc.subject	Project Report - EXTC	en_US
dc.title	Weed and himayaritic of leaf detection system with I.P	en_US
dc.type	Project Report	en_US