The fast computation of Zernike moments from normalized geometric
moments has been developed in this paper. The computation is multiplication
free and only additions are needed to generate Zernike moments. Geometric
moments are generated using Hatamian's filter up to high orders by
a very simple and straightforward computation scheme. Other kinds
of moments (e.g., Legendre, pseudo Zernike) can be computed using
the same algorithm after giving the proper transformations that state
their relations to geometric moments. Proper normalizations of geometric
moments are necessary so that the method can be used in the efficient
computation of Zernike moments. To ensure fair comparisons, recursive
algorithms are used to generate Zernike polynomials and other coefficients.
The computational complexity model and test programs show that the
speed-up factor of the proposed algorithm is superior with respect
to other fast and/or direct computations. It perhaps is the first
time that Zernike moments can be computed in real time rates, which
encourages the use of Zernike moment features in different image
retrieval systems that support huge databases such as the XM experimental
model stated for the MPEG-7 experimental core. It is concluded that
choosing direct computation would be impractical.
%0 Journal Article
%1 Al-Rawi2002
%A Al-Rawi, Mohammed
%A Jie, Yang
%C Beijing, China
%D 2002
%I Institute of Computing Technology
%K Zernike algorithm, digital fast filter, image indexing invariant moment, pattern recognition,
%N 2
%P 181--188
%T Practical Fast Computation of Zernike Moments
%V 17
%X The fast computation of Zernike moments from normalized geometric
moments has been developed in this paper. The computation is multiplication
free and only additions are needed to generate Zernike moments. Geometric
moments are generated using Hatamian's filter up to high orders by
a very simple and straightforward computation scheme. Other kinds
of moments (e.g., Legendre, pseudo Zernike) can be computed using
the same algorithm after giving the proper transformations that state
their relations to geometric moments. Proper normalizations of geometric
moments are necessary so that the method can be used in the efficient
computation of Zernike moments. To ensure fair comparisons, recursive
algorithms are used to generate Zernike polynomials and other coefficients.
The computational complexity model and test programs show that the
speed-up factor of the proposed algorithm is superior with respect
to other fast and/or direct computations. It perhaps is the first
time that Zernike moments can be computed in real time rates, which
encourages the use of Zernike moment features in different image
retrieval systems that support huge databases such as the XM experimental
model stated for the MPEG-7 experimental core. It is concluded that
choosing direct computation would be impractical.
@article{Al-Rawi2002,
abstract = {The fast computation of Zernike moments from normalized geometric
moments has been developed in this paper. The computation is multiplication
free and only additions are needed to generate Zernike moments. Geometric
moments are generated using Hatamian's filter up to high orders by
a very simple and straightforward computation scheme. Other kinds
of moments (e.g., Legendre, pseudo Zernike) can be computed using
the same algorithm after giving the proper transformations that state
their relations to geometric moments. Proper normalizations of geometric
moments are necessary so that the method can be used in the efficient
computation of Zernike moments. To ensure fair comparisons, recursive
algorithms are used to generate Zernike polynomials and other coefficients.
The computational complexity model and test programs show that the
speed-up factor of the proposed algorithm is superior with respect
to other fast and/or direct computations. It perhaps is the first
time that Zernike moments can be computed in real time rates, which
encourages the use of Zernike moment features in different image
retrieval systems that support huge databases such as the XM experimental
model stated for the MPEG-7 experimental core. It is concluded that
choosing direct computation would be impractical.},
added-at = {2011-03-27T19:35:34.000+0200},
address = {Beijing, China},
author = {Al-Rawi, Mohammed and Jie, Yang},
biburl = {https://www.bibsonomy.org/bibtex/2d3148ed2c74eadaf2d5359786f3c46d0/cocus},
interhash = {75d297a32b51d09722e7f02127c94e84},
intrahash = {d3148ed2c74eadaf2d5359786f3c46d0},
issn = {1000-9000},
journaltitle = {#jcst#},
keywords = {Zernike algorithm, digital fast filter, image indexing invariant moment, pattern recognition,},
number = 2,
owner = {CK},
pages = {181--188},
publisher = {Institute of Computing Technology},
timestamp = {2011-03-27T19:35:35.000+0200},
title = {Practical Fast Computation of Zernike Moments},
volume = 17,
year = 2002
}