A Relative Evaluation Of Specificity And Sensitivity In A Diseased Plant Leaf With Hybrid Sift And K-Means Fuzzy Logic Svm Algorithm

Abstract

Early location of the plant infections is basic to maintain a strategic distance from misfortunes in the yield and nature of the farming item. The investigations of the plant illnesses have been generally explored to recognize irregularity in plant development utilizing outwardly discernible examples on the plant. Plant observing and illness location is expected to guarantee maintainability in agriculture. Be that as it may, it is generally hard to screen the plant illnesses physically as they require an ongoing and accurate location. Picture handling is usually utilized for the discovery of plant sicknesses which included picture securing, pre-preparing, division, include extraction, and characterization. In this research paper, A hybrid-based image processing algorithm is proposed to detect diseases on six datasets with plants using its leaves images. The proposed solution focuses on using hybrid k means fuzzy logic SVM and hybrid shift to classify these images. Different parameters are used to compute different algorithms. The results are classified into Sensitivity and specificity.