CROP DISEASE DETECTION USING MACHINE LEARNING APPROACH
Mr.K.Ravi Kumar
Sr. Assistant Professor , IN
N.Durga Sai Priyanka
Sr. Assistant Professor , IN
P. Vasavi
Sr. Assistant Professor , IN
S.Sandeep Kumar Reddy
Sr. Assistant Professor , IN
S.Sai Teja
Sr. Assistant Professor , IN
Keywords: Image processing , SVM classifier, K-means clustering, GLCM
Abstract
Identification of the harvest sicknesses is the way to keeping the misfortunes in the yield and nature of the rural item. The investigations of the harvest ailments mean the investigations of outwardly discernible examples seen on the plant. Well being observing and sickness discovery requires gigantic measure of work, information in the plant ailments, and furthermore require the additionally preparing time. It is hard to screen the plant illnesses, and furthermore there were no fitting systems for this procedure. Thus, picture handling is utilized for the identification of plant ailments. So we can utilize picture preparing for ID of leaf malady in MATLAB. Recognizable proof of illness pursues the means like stacking the picture, differentiate improvement, changing over RGB to HSI, separating of highlights like mean, homogeneity, vitality, connection, entropy and so forth., by utilizing gray level co-occurance matrix properties (GLCM technique) and afterward we use SVM classifier for order. It gives the data to the client in regards to the yield malady.
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