Abstract
A new set of orthogonal moment functions for describing images is
proposed. It is based on the generalized pseudo-Zernike polynomials
that are orthogonal on the unit circle. The generalized pseudo-Zernike
polynomials are scaled to ensure the numerical stability, and some
properties are discussed. The performance of the proposed moments
is analyzed in terms of image reconstruction capability and invariant
character recognition accuracy. Experimental results demonstrate
the superiority of generalized pseudo-Zernike moments compared with
pseudo-Zernike and Chebyshev-Fourier moments in both noise-free and
noisy conditions.
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