• Rahul Nanasaheb Jangle
• Prof. Shilpa A. Sanap

As indicated by the examination and review nation India comprise its vast majority parts as a horticultural part, consequently given the name of rural nation and about 70% of individuals relies upon farming for their endurance. Early recognition of leaf malady is significant exploration point. Different quantities of ailment brought about by growths, microscopic organisms, and nematodes and so on Malady in farming/cultivation crops causes a noteworthy decrease in both amount and nature of agribusiness items. Early recognition of illness and recognizable proof of indications of malady by unaided eye is hard for rancher which results the spreading of sickness in entire yield. Discovery of harvests and its security particularly in enormous ranches is finished by utilizing automated picture handling strategies by taking shading data of leaves. In this introduced an expires identification in plants and yields in fields like performing proposed work. Alternaria Alternata, Anthracnose, Bacterial Blight and others. For the detection using segmentation by K mean clustering. The proposed method shows detection with awfully high accuracy in the different test images.

Multi Class Support Vector Machine(SVM), K Mean Clustering, Colour Features, Image processing, Leaf diseases, Texture features, Gray Level Co-Occurrence Matrix(GLCM),Search Engine Marketing(SEM), and Bacterial Blight

"PLANT LEAF DISEASES DETECTION USING IMAGE PROCESSING BASED SEGMENTATION AND MORPHOLOGICAL OPERATION MULTI LEVEL SVM", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.11, Issue 1, page no.h82-h91, January-2024, Available :http://www.jetir.org/papers/JETIR2401709.pdf

"PLANT LEAF DISEASES DETECTION USING IMAGE PROCESSING BASED SEGMENTATION AND MORPHOLOGICAL OPERATION MULTI LEVEL SVM", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.11, Issue 1, page no. pph82-h91, January-2024, Available at : http://www.jetir.org/papers/JETIR2401709.pdf