Image Segmentation Method for Cotton Mite Disease Based on Color Features and Area Thresholding

Cotton mite disease is a common disease. Taking the cotton mite disease as the research subject, a segmentation method based on color features and area thresholding is proposed under the complex background. The proposed algorithm is comprised of three main steps. First, to extract the analogous disease spots (disease spots and stems) from green plants. Second, some special characteristics are detected in gray histrogram, afterwards convert the segmented images into 8 bit gray-scale images based on single thresholding. Finally, compare the disease spots’ area with stems’ and then segmented binary images by using area thresholding. The experimental results show that this algorithm is of effective in segmenting cotton disease spots; the average correct extraction rate of the algorithm can reach 94.79%.