Revolutionizing Plant Health: A Cutting-Edge Approach to Leaf Disease Detection, Classification and Severity Estimation Through Advanced Image Processing Techniques

In the realm of agriculture, an array of diseases arises from pests and fungi, often necessitating manual identification, a process both time-intensive and prone to inaccuracies. The study advocates for the automation of leaf disease detection through the application of machine learning and image processing. The aim is to alleviate the manual burden associated with monitoring plant leaf conditions. The proposed method entails automated plant leaf disease detection and classification, leveraging image processing and machine learning techniques. Additionally, disease severity estimation is integrated to regulate pesticide usage. The implementation of this approach is slated for MATLAB, harnessing the capabilities of the image processing toolbox and machine learning toolbox.