We analyze two approaches to clustering 2D shapes representing cross-sections of rotationally symmetrical objects. These approaches are based on two ways of shape representation - contours and silhouettes - and a number of similarity measures which are based on a combination of Procrustes analysis (PA) and Dynamic Time Warping (DTW) as well as on binary matrix analysis. The comparison of efficiency of the proposed approaches is performed on datasets of archaeological ceramic vessels.