Curves vs skeletons in object recognition

The type of representation used in describing shape can have a significant impact on the effectiveness of a recognition strategy. Shape has been represented by its bounding curve as well as by the medial axis representation which captures the regional interaction of the boundaries. Shape matching with the former representation is achieved by curve matching, while the latter is achieved by matching skeletal graphs. We compare the effectiveness of these two methods using approaches which we have developed recently for each. The results indicate that skeletal matching involves a higher degree of computational complexity, but is better than curve matching in the presence of articulation or rearrangement of parts. However, when these variations are not present, curve matching is a better strategy due to its lower complexity and roughly equivalent recognition rate.