Plant Leaf Disease Detection using Image Processing

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Abstract

Agriculture, the primary way to produce the food to the people besides its value added to the economy of the country’s gross domestic product. Plants are affected to various diseases and early detection of disease has to be done in order to reduce the social and economical loses. Nowadays farmers are not aware of the type of diseases that affect the plants and the respective measures that have to be taken in order to reduce the effect. This paper focuses on the technique that detects the disease using image processing techniques and providing the measures to the farmers to overcome the disease. The technique is based on the K means clustering which is used to segment the image after that the feature extraction is done based on the Gray level Coocurrence matrix approach then the Support Vector Machine classifier is used to classify the disease with the trained data. We have calculated the percentage of leaf affected and the measurement is done based on it. Here along with disease name its symptoms and measurement are shown.

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APA

Aswitha, B., C.V, R. kumar, & P, V. (2020). Plant Leaf Disease Detection using Image Processing. International Journal of Innovative Technology and Exploring Engineering, 9(7), 409–414. https://doi.org/10.35940/ijitee.f4597.059720

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