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Nowadays many of the farmers and agro help center use the different new technology to enhance the agriculture production. Plants have become important source of energy. There are several diseases that affect plants with the potential to cause economic and social losses. Many of disease are most popular where disease spots occur on the sugar cane plant leaves. If the disease are not detected at first stage than it is more harm full to production. To find out particular disease using Digital image processing helps to find disease and provide prevention for particular disease which types pesticide need to prevent disease. Firstly take Input image in RGB form then the green pixels are removed then the image is segmented useful segment used for extraction finally texture statistics is completed and according to analysis disease prevention is provided. The results suggested that, leaf width, length, perimeter and area related features can be used as factors for prediction, and that machine vision systems lead to successful prediction of targets when fed with appropriate information.

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S.Kavitha Bharathi, & V.Vinothini. (2017). Agricultural plant leaf disease detection and diagnosis using watershed segmentation and gray level co-occurrence matrix (GLCM) . International Journal of Intellectual Advancements and Research in Engineering Computations, 5(2), 1418–1422. Retrieved from