Disease Detection of Plant Leaf Using Image Processing and CNN with Preventive Measures

Most of the diseases on the leaves of plants seriously affect crop yield; thus, their early detection is very necessary for sustainable agriculture. This paper, therefore, proposes an automated system for identifying and classifying leaf diseases by integrating conventional image-processing techniques with a CNN. The developed system enhances leaf images by removing noise, applying color-space transformations, segmenting, and adjusting contrast to enhance disease-specific patterns such as discoloration, variations in texture, and visible lesions. These refined features are subsequently analyzed by a CNN that will correctly identify the disease category. In addition to diagnosis, the system also proposes preventive suggestions based on the identified class of the disease.