An Algorithmic Aspect of Zernike Moments in the Presence of Rotation

Zernike moments are widely used in image processing fields (e.g., rotation-invariant watermarking) based on many desirable properties, such as rotational invariance, noise robust and efficient representation of pattern. In image processing operations, an image after rotation will result in a bigger size for keeping the content. This will cause the difference among Zernike moments of an image and its rotated versions. In this paper, we investigate such a problem in detail and introduce a solution by normalizing original and its rotated versions into the same size. Furthermore, we propose an algorithmic scheme of Zernike moments´ computation. Both theoretical analysis and experimental testing show that the proposed approach can efficiently avoid the effect of the image size change under rotation.