Fourier-based rotation invariant image features

Authors:
Sam Mavandadi;Parham Aarabi;K. N. Plataniotis
Affiliations:
The Edward S. Rogers Sr. Department of Electrical and Computer Engineering, University of Toronto;The Edward S. Rogers Sr. Department of Electrical and Computer Engineering, University of Toronto;The Edward S. Rogers Sr. Department of Electrical and Computer Engineering, University of Toronto
Venue:
ICIP'09 Proceedings of the 16th IEEE international conference on Image processing
Year:
2009

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Abstract

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 [9, 3]. 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.