Volume : 4, Issue : 4, APR 2020


Sreehari R, B Mahalakshmi


Plant disease remains a major threat to food safety. There rapid and immediate identification remains difficult in many parts of the world due to the lack of features and infrastructures. Monitoring of health and disease on plants plays an important role in success of cultivation of crops and plants. In older days’ plant disease detection was done manually by the expertise. This requires tremendous amount of work and excessive processing time. The image processing technique can be used in the plants disease detection. In most of the case disease symptoms are seen on the leaves, stems and fruits. The plant leaf for the detection is considered which shows the disease symptoms. Plant diseases are generally caused by pest, insects, pathogens and decrease the productivity to large scale if not controlled within time. The proposed system intimates the agriculturist about the crop diseases to take further actions. The objective of the proposed system is to early detection of diseases as soon as it starts spreading on the outer layer of the leaves. This project gives the introduction to the plant disease detection and its remedies using machine learning. The proposed system can effectively identify different types of diseases with the ability to deal with complex scenarios from a plant’s area.


Food safety, Convolution Neural Networks, Open cv.

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Article No : 4

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