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DC Field | Value | Language |
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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 |
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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