Plant Disease Detection Using Neural Network - Shraddha; Smitha, P.; Sraddha, P.; Raj, Srisha M.; Shashikala, N. (International Journal of Recent Advances in Multidisciplinary Topics, 2022)
The first step for diagnosing a plant disease is to identify it. This is the foundation for efficient and precise plant disease prevention in a huge-wide environment. In the advancement of technology farming, plant disease identification becomes computerized, giving modern assistance, sharp approach, and preparation. This research is developing a neural network model of plant disease detection and prediction. Most of the time infection occurs in the leaf. The first step in detection is capturing the leaf image. Next these images are preprocessed through image segmentation. Then an image with RGB components is removed and it is converted to a HSV format. Finally, the image of the leaf is converted into black and white. Here White color indicates the defective part of the leaf. Neural network technique is trained to find the disease and healthy leaf. The classifier helps in the early and accurate prediction of leaf diseases.