In this paper a theory of two-dimensional moment invariants for planar
geometric figures is presented. A fundamental theorem is established
to relate such moment invariants to the well-known algebraic invariants.
Complete systems of moment invariants under translation, similitude
and orthogonal transformations are derived. Some moment invariants
under general two-dimensional linear transformations are also included.
Both theoretical formulation and practical models of visual pattern
recognition based upon these moment invariants are discussed. A simple
simulation program together with its performance are also presented.
It is shown that recognition of geometrical patterns and alphabetical
characters independently of position, size and orientation can be
accomplished. It is also indicated that generalization is possible
to include invariance with parallel projection.
%0 Journal Article
%1 Hu1962
%A Hu, Ming-Kuei
%D 1962
%K Image Pattern analysis, null recognition
%N 2
%P 179-187
%T Visual pattern recognition by moment invariants
%V 8
%X In this paper a theory of two-dimensional moment invariants for planar
geometric figures is presented. A fundamental theorem is established
to relate such moment invariants to the well-known algebraic invariants.
Complete systems of moment invariants under translation, similitude
and orthogonal transformations are derived. Some moment invariants
under general two-dimensional linear transformations are also included.
Both theoretical formulation and practical models of visual pattern
recognition based upon these moment invariants are discussed. A simple
simulation program together with its performance are also presented.
It is shown that recognition of geometrical patterns and alphabetical
characters independently of position, size and orientation can be
accomplished. It is also indicated that generalization is possible
to include invariance with parallel projection.
@article{Hu1962,
abstract = { In this paper a theory of two-dimensional moment invariants for planar
geometric figures is presented. A fundamental theorem is established
to relate such moment invariants to the well-known algebraic invariants.
Complete systems of moment invariants under translation, similitude
and orthogonal transformations are derived. Some moment invariants
under general two-dimensional linear transformations are also included.
Both theoretical formulation and practical models of visual pattern
recognition based upon these moment invariants are discussed. A simple
simulation program together with its performance are also presented.
It is shown that recognition of geometrical patterns and alphabetical
characters independently of position, size and orientation can be
accomplished. It is also indicated that generalization is possible
to include invariance with parallel projection.},
added-at = {2011-03-27T19:35:34.000+0200},
author = {Hu, Ming-Kuei},
biburl = {https://www.bibsonomy.org/bibtex/24bb2ed552d3278208938f4f68417efdf/cocus},
file = {:./hu.pdf:PDF},
interhash = {4b4427fd5faf18ad9083ca338b09b129},
intrahash = {4bb2ed552d3278208938f4f68417efdf},
issn = {0018-9448},
journaltitle = {#ieeeti#},
keywords = {Image Pattern analysis, null recognition},
number = 2,
pages = { 179-187},
timestamp = {2011-03-27T19:35:40.000+0200},
title = {Visual pattern recognition by moment invariants},
volume = 8,
year = 1962
}