3D geometric moment invariants from the point of view of the classical invariant theory
Abstract
The aim of this paper is to clear up the problem of the connection between the 3D geometric moments invariants and the invariant theory, considering a problem of describing of the 3D geometric moments invariants as a problem of the classical invariant theory.
Using the remarkable fact that the complex groups $SO(3,\mathbb{C})$ and $SL(2,\mathbb{C})$ are locally isomorphic, we reduced the problem of deriving 3D geometric moments invariants to the well-known problem of the classical invariant theory.
We give a precise statement of the 3D geometric invariant moments computation, intro\-ducing the notions of the algebras of simultaneous 3D geometric moment invariants, and prove that they are isomorphic to the algebras of joint $SL(2,\mathbb{C})$-invariants of several binary forms. To simplify the calculating of the invariants we proceed from an action of Lie group $SO(3,\mathbb{C})$ to equivalent action of the complex Lie algebra $\mathfrak{sl}_2$. The author hopes that the results will be useful to the researchers in the
fields of image analysis and pattern recognition.
References
S.F. Pratama, A.K. Muda, Y.-H. Choo, J. Flusser, A. Abraham, ATS drugs molecular structure
representation using refined 3D geometric moment invariants, J. Math. Chem., 55 (2017), 1951–1963.
A. Abdalbari, J. Ren, V. Green, Seeds classification for image segmentation based on 3-D affine moment invariants, Biomed. Eng. Lett., 6 (2016), 224–233.
M. Zucchelli, S. Deslauriers-Gauthier, R. Deriche, A computational Framework for generating rotation invariant features and its application in diffusion MRI, Medical Image Analysis, 60 (2020), 101597.
F.A. Sadjadi, E.L. Hall, Three-dimensional moment invariants, IEEE Transactions on Pattern Analysis and Machine Intelligence, (2) (1980), 127–136.
X. Guo, Three dimensional moment invariants under rigid transformation. In: Chetverikov D., Kropatsch W.G. (eds), Computer Analysis of Images and Patterns, CAIP 1993, Lecture Notes in Computer Science, 719 (1993), Springer, 518–522.
C.-H. Lo, H.-S. Don, 3-D moment forms: their construction and application to object identification and positioning, IEEE Trans. Pattern Anal. Mach. Intell., 11 (1989), №10, 1053–1064.
T. Suk, J. Flusser, J. Boldyˇs, 3D rotation invariants by complex moments, Pattern Recognition, 48 (2015), №11, 3516–3526.
J. Flusser, T. Suk, B. Zitova, 2D and 3D image analysis by moments, Wiley, Berlin, 2017.
T. Suk, J. Flusser, Tensor method for constructing 3D moment invariants, In: Real P., Diaz-Pernil D., Molina-Abril H., Berciano A., Kropatsch W. (eds) Computer Analysis of Images and Patterns, CAIP 2011, Lecture Notes in Computer Science, 6855, Springer, Berlin, 2011.
G. Burel, H. Henocq, Three-dimensional invariants and their application to object recognition, Signal Processing, 45 (1995), 1–22.
M.K. Hu, Visual pattern recognition by moment invariants, IRE Trans. Inform. Theory, 8 (1962), №2, 179–187.
B. Yang, J. Flusser, T. Suk, 3D rotation invariants of Gaussian–Hermite moments, Pattern Recognition Letters, 54 (2015), №1, 18–26.
L. Bedratyuk, 2D geometric moment invariants from the point of view of the classical invariant theory, Journal of Mathematical Imaging and Vision, 62 (2020), 1062–1075.
M. Olive, About Gordan’s algorithm for binary forms, Foundations of Computational Mathematics, 17 (2017), №6, 1407–1466.
P. Woit, Quantum Theory, Groups and representations, Springer, Berlin, 2014.
B. Hall, Quantum Theory for Mathematicians. Springer, Berlin, 2013.
L. Bedratyuk, The Maple package for SL2-invariants and kernel of Weitzenb¨ock derivations, arXiv: 1101.0622v1, 2011.
L. Bedratyuk, The Maple package for calculating Poincar´e series, arXiv: 1006.5372, 2010.
W. Fulton, J. Harris, Reptesentation theory: a first course, Springer-Verlag, New York, 1991.
H. Weyl, The classical groups: their invariants and representations, Princeton university press, 1946.
Copyright (c) 2022 L. Bedratyuk, A. Bedratyuk
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
Matematychni Studii is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) license.