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Banana leaf disease detection using K-means clustering and Feature extraction techniques

Vandana V. Chaudhari, Manoj P. Patil

202038 citationsDOI

Abstract

In India, most of the people survive their life on farming. Farmers face many difficulties due to climate changes. One of them is loss in the yield and one of the reasons behind that is the diseases appear on the plant. Getting the expert eye necked opinion is not possible for all the farmers. There is need to recognize the disease in early stage using easiest way. Automated disease recognition can be done using image processing techniques and machine learning techniques. This work explains the automated system to identify the banana plant diseases by extracting color, shape and texture features. Support Vector Machine (SVM) Classification Techniques is used for classification of data. Proposed work showed the average accuracy of 85 % to identify four kinds of diseases as sigatoka, cmv, bacterial wilt and panama.

Topics & Concepts

Support vector machineComputer scienceArtificial intelligenceFeature extractionPlant diseaseCluster analysisk-means clusteringPattern recognition (psychology)Contextual image classificationFace detectionMachine learningFacial recognition systemImage (mathematics)BiotechnologyBiologySmart Agriculture and AIBanana Cultivation and ResearchSpectroscopy and Chemometric Analyses
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