Cotton Leaf Disease Detection Through Image Processing Technique - Thamballa Aruna,; G.V.S. Ananthnath, (International Journal of Scientific Research in Computer Science, Engineering and Information Technology, 2025)
Agriculture is an important industry in many countries. As farm production is a large part of India's financial system, it is extremely important to carefully examine the issues of food production. The scientific and economic importance of nomenclature and recognition of plant infections are increasing, There is a need for a method or system that can automatically diagnose diseases because it can revolutionize surveillance. You can ingest huge harvest fields and plant leaves. Diagnosis of cotton disease is important to prevent catastrophic outbreaks. Immediately after the detection of disease, the purpose of this study is to issue guidelines for the creation of applications to detect wattage blade disease. To use this, the user must first submit a photo of the cotton blade and then use image processing to obtain a digitized color image of the damaged sheet. Get a digitized color image of this sheet. This can be handled using a mobile set algorithm to expect the true cause of wattage blade disease.
Keywords: Cotton plant; Cotton leaf; Disease; Detection; MobileNet; Feature extraction; Image classification