Fuzzy C-means clustering is one of the important learning algorithms in the field of pattern recognition, which has been applied early to image segmentation. Without considering the spatial information of images, the original fuzzy C-means algorithm is very sensitive to image noise. Lots of robust fuzzy C-means algorithms have been proposed in the literature to solve this problem. A general solution is to add the spatial information to the object function of fuzzy C-means. This paper describes the way of embedding the spatial information and shows the advantages and disadvantages of this method.