Moment invariants have been proposed as pattern sensitive features
in classification and recognition applications. In this paper, the
authors present a comprehensive study of the effectiveness of different
moment invariants in pattern recognition applications by considering
two sets of data: handwritten numerals and aircrafts. The authors
also present a detailed study of Zernike and pseudo Zernike moment
invariants including a new procedure for deriving the moment invariants.
In addition, the authors introduce a new normalization scheme that
reduces the large dynamic range of these invariants as well as implicit
redundancies in these invariants. Based on a comprehensive study
with both handwritten numerals and aircraft data, the authors show
that the new method of deriving Zernike moment invariants along with
the new normalization scheme yield the best overall performance even
when the data are degraded by additive noise.
%0 Journal Article
%1 Belkasim91
%A Belkasim, S. O.
%A Shridhar, M.
%A Ahmadi, M.
%D 1991
%K moments, shape-feature
%N 12
%P 1117--1138
%R http://dx.doi.org/10.1016/0031-3203(91)90140-Z
%T Pattern recognition with moment invariants: A comparative study and
new results
%U http://dx.doi.org/10.1016/0031-3203(91)90140-Z
%V 24
%X Moment invariants have been proposed as pattern sensitive features
in classification and recognition applications. In this paper, the
authors present a comprehensive study of the effectiveness of different
moment invariants in pattern recognition applications by considering
two sets of data: handwritten numerals and aircrafts. The authors
also present a detailed study of Zernike and pseudo Zernike moment
invariants including a new procedure for deriving the moment invariants.
In addition, the authors introduce a new normalization scheme that
reduces the large dynamic range of these invariants as well as implicit
redundancies in these invariants. Based on a comprehensive study
with both handwritten numerals and aircraft data, the authors show
that the new method of deriving Zernike moment invariants along with
the new normalization scheme yield the best overall performance even
when the data are degraded by additive noise.
@article{Belkasim91,
abstract = {Moment invariants have been proposed as pattern sensitive features
in classification and recognition applications. In this paper, the
authors present a comprehensive study of the effectiveness of different
moment invariants in pattern recognition applications by considering
two sets of data: handwritten numerals and aircrafts. The authors
also present a detailed study of Zernike and pseudo Zernike moment
invariants including a new procedure for deriving the moment invariants.
In addition, the authors introduce a new normalization scheme that
reduces the large dynamic range of these invariants as well as implicit
redundancies in these invariants. Based on a comprehensive study
with both handwritten numerals and aircraft data, the authors show
that the new method of deriving Zernike moment invariants along with
the new normalization scheme yield the best overall performance even
when the data are degraded by additive noise.},
added-at = {2011-03-27T19:35:34.000+0200},
author = {Belkasim, S. O. and Shridhar, M. and Ahmadi, M.},
biburl = {https://www.bibsonomy.org/bibtex/2387275f7f53c093dc9cb1298aed3e9e9/cocus},
citeulike-article-id = {3191430},
doi = {http://dx.doi.org/10.1016/0031-3203(91)90140-Z},
interhash = {14ba406d41adc6c540d986ec26a96a06},
intrahash = {387275f7f53c093dc9cb1298aed3e9e9},
journaltitle = {#PR#},
keywords = {moments, shape-feature},
number = 12,
owner = {CK},
pages = {1117--1138},
posted-at = {2008-09-04 12:54:23},
priority = {1},
timestamp = {2011-03-27T19:35:35.000+0200},
title = {Pattern recognition with moment invariants: A comparative study and
new results},
url = {http://dx.doi.org/10.1016/0031-3203(91)90140-Z},
volume = 24,
year = 1991
}