Automatic classification of paddy leaf disease

Abstract

RiceisastaplefoodinmostoftheAsiancountries.Itisanimportantcrop, andoverhalfoftheworldpopulationreliesonitforfood.However,paddy leafdiseasecanaffectboththequalityandquantityofpaddyinagriculture production.Theclassificationofpaddyleafdiseaseisanimportantand urgenttaskasitdestroysabout10%to15%ofproductioninAsia.Thus,a studyonautomaticclassificationofpaddyleafdiseaseusingimage processingispresented.Featureextractiontechniquesofcolor,texture,and shapewereimplementedtoanalyzethecharacteristicsofthepaddyleaf disease.Inanother note,aSupportVector Machine(SVM)isused toclassify thefourtypesofpaddyleafdiseasewhicharethebrownspot,bacterialleaf blight,tungrovirus,andleaf scald.Theperformanceofthe proposedstudyis evaluatedto160testingimageswhichreturned86.25%ofclassification accuracy.Theoutcomeofthisstudyisexpectedtoassisttheagrotechnology industryinearlydetectionofpaddyleafdiseaseinwhichanappropriate actioncould be taken accordingly.