In this paper, we propose a method for identifying a discrete planar symmetric shape from an arbitrary viewpoint. Our algorithm is based on a newly proposed notion of a view's skeleton. We show that this concept yields projective invariants which facilitate the identification procedure. It is, furthermore, shown that the proposed method may be extended to the case of noisy data to yield an optimal estimate of a shape in question. Substantiating examples are provided.