Abstract
Recently, some statistical studies have been done using the shape data. One
of these studies is clustering shape data, which is the main topic of this paper. We are
going to study some clustering algorithms on shape data and then introduce the best
algorithm based on accuracy, speed, and scalability criteria. In addition, we propose
a method for representing the shape data that facilitates and speeds up the shape
clustering algorithms. Although the mentioned method is not very accurate, it is fast;
therefore, it is useful for datasets with a high number of landmarks or observations,
which take a long time to be clustered by means of other algorithms. It should be noted
that this method is not new, but in this article we apply it in shape data analysis.
