Abstract: India is a farming country, more than 70% of our people rely on agriculture. A third of our domestic revenue comes from farming. The farmers face failure because of different cultivable diseases, and farmers are reluctant to keep an eye on their crops when the region is enormous (acres). In agriculture, the diagnosis of plant diseases thus plays an important part. In order to achieve loss caused due to crop diseases which adversely affect crop quality and yield, timely and exact identification of diseases is necessary. Early identification and intervention will mitigate plant disease loss and excessive use of medicinal products. Previously, image recognition automatically detected plant disease. We propose machine learning mechanisms and image recognition methods for the identification and classification of diseases. Crop disease is detected in different processing phases including the collection of images, image pre- processing and the retrieval of images & classification of features. And also send Fertilizers as the output. We can use global image extraction techniques for the extraction of image features.
Keyword: - Deep Learning, Global Features, Classification, Image Processing.
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DOI:
10.17148/IJARCCE.2021.101233
