Plant Disease Detection Using Image Processing

Identifying plant diseases visually is a time-consuming and often imprecise task, limited to specific regions. Conversely, employing automatic detection techniques streamlines the process, reducing labor and time while enhancing accuracy. Common plant ailments, such as brown and yellow spots, early and late scorch, as well as fungal, viral, and bacterial infections, can be effectively identified through image processing. This involves assessing the affected area's size and color disparity using techniques like image acquisition, preprocessing, segmentation, feature extraction, and classification. Therefore, this project focuses on utilizing leaf images to detect and diagnose plant diseases efficiently.