Object recognition by combining viewpoint invariant Fourier descriptor and convex hull

It is observed that the shape recognition process that uses global information would fail when dealing with occlusion. In this paper, an algorithm that combines the methods of viewpoint invariant Fourier descriptor and convex hull is presented for recognizing 3D planar objects by their contours. Invariants are calculated from a set of local segments extracted from the convex hull of a shape. Under such approach, an object is represented by sets of invariant points instead of a single point in a 2D parameter space of I/sub 1/ and I/sub 2/. The method is efficient and yields a high recognition rate in recognizing partially occluded objects. Classification can be carried out correctly even when the convex hull of the object has changed as a result of occlusion.