K-​​​Means clustering

K-​​​means cluster process is applied to the image to do cluster analysis. It is the best method to solve problems related to clustering of the best learning algorithms that solve the clustering problems. K-​​​means algorithm is used to detect the iterative K-​​​centers. The sum of distances of the data points is optimized from their centers. In many applications, the K-​​​means algorithm of clustering is used to segment the paddy leaf image into many clusters of disease. Figure 6.5 shows the output of the K-​​​means cluster algorithm for a leaf infected with the disease.