LEAF DISEASE IDENTIFICATION AND CLASSIFICATION USING K-MEANS CLUSTERING

Agricultural productivity is something on which economy highly depends. Plants are main source of food. This is the one of the reasons that disease detection in plants plays an important role in agriculture field, as having disease in plants are quite natural. If proper care is not taken in this area then it causes serious effects on plants and due to which respective product quality, quantity or productivity is affected. It is very difficult to monitor the plant diseases manually. It requires tremendous amount of work, expertise in the plant diseases, and also require the excessive processing time. Detection of plant disease through some automatic technique is beneficial as it reduces a large work of monitoring in big farms of crops, and at very early stage itself it detects the symptoms of diseases i.e. when they appear on plant leaves. So, we introduced a modern technique to find out disease related to leaf. Hence, image processing is used for fast and accurate disease detection of plant. Disease detection involves the steps like image acquisition, image pre-processing, image segmentation, feature extraction and classification. We developed k-means clustering algorithm with multi SVM algorithm in MATLAB software for disease identification and classification