Analysis on Classification and Prediction of Leaf Disease using Deep Neural Network and Image Segmentation Technique

Abstract

Agriculture is a big source of income in states like India. This paper examines leaf parameter analysis, the identification of healthy, ill, or affected leaf regions, and the classification of leaf diseases using various methods for different plants. The ability of human eyes to identify the exact form of leaf disease is critical and difficult. The algorithm created for one plant does not work correctly with the leaf of another plant. Along with the leaf parameter analyzer, specialized plant algorithms are needed to detect leaf diseases. Image processing and machine learning methods are useful for accurately identifying leaf disease. With image segmentation ,this model provides results more accurately using cluster sizes which has been experimentally optimized . In agriculture, early disease detection is crucial for optimizing crop yield. Crop quality is affected by diseases such asseptoria leaf spot, bacterial spot yellow curved leaf, bacterial spot.this paper uses (CNN)Convolution Neural Network and (DCNN) Deep Convolution Neural Network