78.7%。Aiming at the severe occluding of leaves of weed and wheat, a weed identification method that applied to improved hierarchical approach to color image segmentation by using homogeneity and combines color and morphological features was presented. Color feature has been utilized to distinguish plants and background: using a method that took YIQ as color-space and Ias characteristic variant and improved method of maximum classes square error as criterion; color feature has been utilized to distinguish wheat and weed: using a method that took HSI as color-space and homogeneity of I and S as characteristic variant separately and hierarchical homogeneity segmentation as criterion; ultimately morphological feature has been utilized to obtain weed: using a method that combined morphological opening and closing filter and AND operation algorithm. The proposed methods together with a chemical weeding system were simulated and the efficiency of the overall systems was evaluated theoretically. Experiments on a serial of weed images were conducted. The experimental results showed that the correct identification ratio exceeds 92.6%, the herbicide reduction rate of single image ranged from 35% to 50%，the herbicide reduction rate of the whole wheat field exceeded 78.7%. 