Image Processing System based Identification and Classification of Leaf Disease: A Case Study on Paddy Leaf

Paddy is the main nourishment in the south sections of India. It straightforwardly influences the country's infrastructure. Bacterial leaf blight, brown spot and leaf smut were its main illnesses found in paddy field crops, which also significantly affect its profitability. This work presents an image processing system based automatic identification and classification of various paddy leaf diseases by affecting the cultivation of paddy namely bacterial leaf blight, brown spot, and leaf smut. The key phases of proposed methodology are pre-processing of images, segmentation, feature extraction and classification. The technique used in the proposed work to identify paddy leaf disease involves Otsu threshold method for segmentation, grey level co-occurrence metrics for feature extraction and k-nearest neighbors algorithm for classification. The proposed system aims at achieving rapid and accurate identification of disease and classification of the disease type and also helps in classifying the various paddy leaf diseases by utilizing the texture and shape features that majorly contributes in leaf disease recognition.