Symptom-Based Identification of G-4 Chili Leaf Diseases Based on Rotation Invariant - Das Chagas Silva Araujo, Sufola; Malemath, V. S.; Sundaram, K. Meenakshi (Frontiers in Robotics and AI, 2021)
Automatic detection of diseases by just checking the symptoms on the plant leaves makes it easier and cheaper to diagnose different disease. This describes the way in which the symptoms of the diseased plants are detected by using the concept of image processing. The manual way of detecting these symptoms and diagnosing the disease is very time consuming and has more chances of making mistakes. This method is develop to identify the symptoms when a plant image is given as an input. The methodology used is, image acquisition, segmentation, training and testing images, symptoms extraction of the plant image, Building of the symptoms vector feature dataset, and finding the correlation and similarity between different symptoms of the plant. This will detect the different disease of the plant