Zernike moments have been proven to be very powerful image descriptors.
However, their computational complexity makes them unsuitable for
real-time applications. In this paper, a mathematical relationship
between geometric and Zernike moments is extracted. In this way,
the computation of geometric moments is adequate to derive Zernike
moments. Since geometric moments can be efficiently implemented in
hardware and their calculation can be performed in real-time, we
propose here a new real-time hardware architecture for the computation
of Zernike moments. This method outperforms existing software approaches,
especially for large images, allowing real-time processing of images
up to 4 Mpixels.
%0 Journal Article
%1 Kotoulas2005
%A Kotoulas, L.
%A Andreadis, I.
%D 2005
%K FPGA, Zernike arrays, complexity, computation computational descriptor, field gate geometric image method moment, moments of polynomials, processing, programmable real-time retrieval,
%N 6
%P 801--809
%R 10.1109/TCSVT.2005.848302
%T Real-time computation of Zernike moments
%V 15
%X Zernike moments have been proven to be very powerful image descriptors.
However, their computational complexity makes them unsuitable for
real-time applications. In this paper, a mathematical relationship
between geometric and Zernike moments is extracted. In this way,
the computation of geometric moments is adequate to derive Zernike
moments. Since geometric moments can be efficiently implemented in
hardware and their calculation can be performed in real-time, we
propose here a new real-time hardware architecture for the computation
of Zernike moments. This method outperforms existing software approaches,
especially for large images, allowing real-time processing of images
up to 4 Mpixels.
@article{Kotoulas2005,
abstract = { Zernike moments have been proven to be very powerful image descriptors.
However, their computational complexity makes them unsuitable for
real-time applications. In this paper, a mathematical relationship
between geometric and Zernike moments is extracted. In this way,
the computation of geometric moments is adequate to derive Zernike
moments. Since geometric moments can be efficiently implemented in
hardware and their calculation can be performed in real-time, we
propose here a new real-time hardware architecture for the computation
of Zernike moments. This method outperforms existing software approaches,
especially for large images, allowing real-time processing of images
up to 4 Mpixels.},
added-at = {2011-03-27T19:35:34.000+0200},
author = {Kotoulas, L. and Andreadis, I.},
biburl = {https://www.bibsonomy.org/bibtex/29f255c247fa08dda40e284e8d3572e1c/cocus},
doi = {10.1109/TCSVT.2005.848302},
interhash = {5748fa214b30a6452981b8db6f03d5cb},
intrahash = {9f255c247fa08dda40e284e8d3572e1c},
issn = {0000-0000},
journaltitle = {#ieeetcsvt#},
keywords = {FPGA, Zernike arrays, complexity, computation computational descriptor, field gate geometric image method moment, moments of polynomials, processing, programmable real-time retrieval,},
number = 6,
owner = {CK},
pages = {801--809},
timestamp = {2011-03-27T19:35:41.000+0200},
title = {Real-time computation of Zernike moments},
volume = 15,
year = 2005
}