Journal
PATTERN RECOGNITION
Volume 47, Issue 8, Pages 2596-2606Publisher
ELSEVIER SCI LTD
DOI: 10.1016/j.patcog.2014.02.014
Keywords
Exponent-Fourier moments; Zernike moments; Image analysis; Bessel-Fourier moments; Radial harmonic Fourier moments; Polar Harmonic Transforms
Funding
- National Natural Foundation of China [61065004, 61202285]
- Key Science&Technology Research Fund of Henan Provincial Educational Department [148520020, 13A520033]
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In this paper, we propose a new set of orthogonal moments based on Exponent functions, named Exponent-Fourier moments (EFMs), which are suitable for image analysis and rotation invariant pattern recognition. Compared with Zernike polynomials of the same degree, the new radial functions have more zeros, and these zeros are evenly distributed, this property make EFMs have strong ability in describing image. Unlike Zernike moments, the kernel of computation of EFMs is extremely simple. Theoretical and experimental results show that Exponent-Fourier moments perform very well in terms of image reconstruction capability and invariant recognition accuracy in noise-free, noisy and smooth distortion conditions. The Exponent-Fourier moments can be thought of as generalized orthogonal complex moments. (C) 2014 Published by Elsevier Ltd.
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