Image segmentation is the first important step to image analysis and image processing. In this paper, according to color
crops image characteristics, we firstly transform the color space of image from RGB to HIS, and then select proper initial
clustering center and cluster number in application of mean-variance approach and rough set theory followed by
clustering calculation in such a way as to automatically segment color component rapidly and extract target objects from
background accurately, which provides a reliable basis for identification, analysis, follow-up calculation and process of
crops images. Experimental results demonstrate that improved k-means clustering algorithm is able to reduce the
computation amounts and enhance precision and accuracy of clustering.