Leaf Disease Detection and Grading using Image Processing
In agriculture sector automatic leaf disease detection is essential research topic as it may prove benefits in monitoring huge fields of crops, and thus automatically detect disease as soon as grading it. There are the principle ventures for disease discovery of Image Acquisition, Image Preprocessing, Image Segmentation, Feature Extraction and Statistical Analysis. The proposed system is separated into two stages, in first stage the plant is perceived on the premise of the Feature of leaf, it incorporates Preprocessing of leaf pictures, and Feature extraction taken after by Artificial Neural Network based training and classification for acknowledgment of leaf. In second stage the malady show in the leaf is classify, this procedure incorporates K-Means based segmentation of defected area , Feature extraction of abandoned segment and the ANN based classification of disease. At that point the disease grading is done using fuzzy logic on the premise of the amount of disease introduce in the leaf.