The document discusses the preprocessing stages for leaf disease detection which include reading images, image preprocessing like enhancement and segmentation, and feature extraction and classification. The preprocessing steps are outlined which involve histogram equalization, resizing, color transformation, k-means clustering to segment healthy and diseased portions, converting to HSI color space, extracting features using GLCM, and using SVM for recognition. K-means clustering is described as partitioning images into clusters based on centroid, mean intensity and area to minimize total cluster variance.