A segmentation improved robust PNN model for disease identification in different leaf images

Agricultural Images are defined for different fruits, crops, vegetables and flowers to identify the agricultural product type or the associated disease identification. These diseases are specific to the product component which can be leaf, root, seed etc. This automation is helpful to provide the identification of disease from remote lab. This paper is defined specifically for leaf disease identification. The work is here divided in two major stages. In first stage, the ring project based segmentation model is defined to explore the features of leaf images. Once the features are identified, the next work is to apply the PNN classifier to identify the existence disease. The work is about to identify the health and infected disease based on featured region identification. The work is applied on randomly collected leaf images from web for different plants. The simulation results show the clear and accurate identification of disease leaf.