Classification of Automatic Detection of Plant Disease in Leaves and Fruits using Image Processing with Convolutional Neural Network

Detection and identification of disease in plants is the fundamental step to avoid various constraints and to enhance productivity. In agricultural farm, the crops are prone to various bacterial and fungal disease. It is initiated due to the varied ecological conditions and soil categories. The earlier prediction of diseases helps to prevent the complete degradation of crops. The disease is detected through small patches on the leaves of the plant. The evolution of automation and innovations helps in the earlier detection of disease in the leaves and fruits of the crops. It is achieved by artificial intelligence. This is done through the image processing techniques. It uses the comparison of healthy plant leaves to that of the infected leaves and fruits. The classification of disease in the fruits and leaves are done accurately through the convolution neural network. This helps to detect the type and cause of the bacterial and fungal infections. This includes image pre-processing, data acquisition and image classification with feature extraction. Thus the CNN model helps to detect and classify the disease in plant and fruits in agricultural farm.