Abstract
The computation of Zernike radial polynomials contributes most of
the computation time in computing the Zernike moments due to the
involvement of factorial terms. The common approaches used in fast
computation of Zernike moments are Kintner's, Prata's, coefficient
and q-recursive methods. In this paper, we propose faster methods
to derive the full set of Zernike moments as well as a subset of
Zernike moments. A hybrid algorithm that uses Prata's, simplified
Kintner's and coefficient methods is used to derive the full set
of Zernike moments. In the computation of a subset of Zernike moments,
we propose using the combination of Prata's, simplified Kintner's,
coefficient and q-recursive methods. Fast computation is achieved
by using the recurrence relations between the Zernike radial polynomials
of successive order without any involvement of factorial terms. In
the first and second experiments, we show both the hybrid algorithms
take lesser computation time than the existing methods in computing
the full set of Zernike moments and a selected subset of Zernike
moments which are not in successive sequence. Both hybrid algorithms
have been applied in real world application in the classification
of rice grains using full set and subset of Zernike moments. The
classification performance using optimal subset of Zernike moments
is better than using full set of Zernike moments.
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