Identification and Detection of Plant Leaf Diseases Using Python
Prof. Nicky Balani, Jayshri Raut, Neha Doye, Trupti Gaikwad, Vaishnavi Kalamkar
Electronics and Telecommunication Engineering, S.B Jain Institute of Technology Management and Research, Nagpur-441501, Maharashtra, India
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Abstract
India is an agricultural country where in most of the population depends on agriculture. Research in agriculture is aimed towards increase of productivity and food quality at reduced expenditure, with increased profit. Agricultural production system is an outcome of a posh interaction of soil, seed, and agro chemicals. so as to get more valuable products, a product internal control is essentially mandatory. Many studies show that quality of agricultural products could also be reduced thanks to plant diseases. Diseases are impairment to the traditional state of the plant that modifies or interrupts its vital functions like photosynthesis, transpiration, pollination, fertilization, germination etc. These diseases are caused by pathogens viz., fungi, bacteria and viruses, and thanks to adverse environmental conditions. Farmers encounter great difficulties in detecting and controlling plant diseases. Thus, it's of great importance to diagnose the plant diseases at early stages so appropriate and timely action may be taken by the farmers to avoid further losses. The paper focuses on the approach supported image processing for detection of diseases of plants. web application is employed that helps farmers for identifying disease by uploading a leaf image to the system. The system encompasses a set of algorithms which might identify the kind of disease. Input image given by the user undergoes several processing steps to detect the disease and results are returned back to the user via web application.
Key Words: Image processing, Detection, Identification ,diseases, Convolutional neural network, segmentation, feature extraction, classification.
