Spherical harmonic descriptor for gray-level image similarity matching

In this paper, we present a new spherical harmonics-based descriptor for matching the shape similarity between two gray-level images. We describe the properties of this descriptor and show how it can be applied to match the shape similarity between two gray-level images. The advantages of this descriptor are two-fold. First, the spherical harmonic descriptor is invariant to rotation. Second, the spherical harmonic descriptor is a 3D descriptor, which in turn makes comparison of the two gray-level images more efficient.