Abstract: In order to achieve the automated nondestructive monitoring of sorghum leaf disease spot, the author uses support vector machine (SVM) technology to research automatic segmentation and extraction of sorghum leaf disease spot image. The results showed that selecting the color feature values of the 3 kinds of color spaces (RGB, HIS and Lab) could eliminate the influence of the light brightness when you took a photo. In the MATLAB software environment using LIBSVM software to establish support vector machine (SVM) classification model of disease spot image pixels and background image pixels, could implement disease spot image efficient segmentation and high-quality extraction. The disease spot image which was extracted automatically by programs could closely match the recognition by the human eye. If using a large number of sampled disease spot image to train model, could achieve the disease spot image fully automated segmentation, extraction and determination. So this research has very important significance to build fully automated crop disease spot image recognition system.