Fourier-based Rotation Invariant image features

Fourier Coefficients have long been used to achieve invariance to signal transformations. For the purposes of image processing, the magnitude of the Fourier transform has been used in conjunction with other transforms to achieve invariance to rotation. In this paper we propose a Rotation Invariant Descriptor for matching images based on features derived from the Discrete Fourier Transform (DFT). The features combine both the phase and the magnitude information to achieve invariance. Experiments are conducted to show the robustness of these features under changes of scale and compression of images.