Awareness of Identification of Plant Leaf Diseases in Cotton Fields with the Applications of Image Processing Techniques

This study highlights the threat of crop diseases, especially in cotton, to food security in developing nations. Identifying similar-looking leaf diseases requires costly, time-consuming visual analysis by experts. Early diagnosis is crucial to boosting agricultural yields. An image processing system, combined with preprocessing techniques like augmentation, background elimination, and filtering, enhances disease detection. Texture and color-based feature extraction, along with SVM classification and ANN models, improve accuracy. Advanced technologies like image processing and machine learning enable early detection, precise health monitoring, and increased agricultural productivity.