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@article{152153,
        author = {Sachin Patel and Ashay Srivastava and Aniket Keshri and Renu Rani and Charu Tyagi},
        title = {Plant Disease Detection Using Image Processing},
        journal = {International Journal of Innovative Research in Technology},
        year = {},
        volume = {8},
        number = {2},
        pages = {575-578},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=152153},
        abstract = {The economy of the country depends on the productivity of the agricultural sector. In India, it is a civilized country, and about 70% of the population is dependent on agriculture. Farmers have a wide range of diversity to select from a variety of suitable crops, and the search for a suitable pesticides for your plants. Any damage to the installation due to disease, leads to a significant decrease in both the quantity and quality of agricultural products. The identification of the plant diseases is the key to preventing the loss of productivity and the improvement of the quality of the products. The traditional methods are reliable but require human resources for the visual observation of the plant's leaves, patterns, and disease diagnosis. The study of plant means to study the observable trends in the plant. The Monitoring of the health of the plants, and the diagnosis of the disease is of great significance for sustainable agriculture. It is very difficult to control the growth of the plants by hand. It takes a tremendous amount of work and research in the plant, and it requires excessive processing time. Hence, image processing is used for the detection of plant pathogens. Diagnosis of the disease involves the steps like image acquisition, data processing, image segmentation, feature extraction, and classification.},
        keywords = {Image Processing, Image acquisition, Segmentation, Feature-extraction.},
        month = {},
        }