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Radial invariant of 2D and 3D Racah moments

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An Erratum to this article was published on 08 August 2017

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Abstract

In this paper, we introduce new sets of 2D and 3D rotation, scaling and translation invariants based on orthogonal radial Racah moments. We also provide theoretical mathematics to derive them. Thus, this work proposes in the first case a new 2D radial Racah moments based on polar representation of an object by one-dimensional orthogonal discrete Racah polynomials on non-uniform lattice, and a circular function. In the second case, we present new 3D radial Racah moments using a spherical representation of volumetric image by one-dimensional orthogonal discrete Racah polynomials and a spherical function. Further 2D and 3D invariants are extracted from the proposed 2D and 3D radial Racah moments respectively will appear in the third case. To validate the proposed approach, we have resolved three problems. The 2D/ 3D image reconstruction, the invariance of 2D/3D rotation, scaling and translation, and the pattern recognition. The result of experiments show that the Racah moments have done better than the Krawtchouk moments, with and without noise. Simultaneously, the mentioned reconstruction converges rapidly to the original image using 2D and 3D radial Racah moments, and the test 2D/3D images are clearly recognized from a set of images that are available in COIL-20 database for 2D image, and PSB database for 3D image.

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  • 08 August 2017

    An erratum to this article has been published.

References

  1. Canterakis N (1999) 3D Zernike moments and Zernike affine invariants for 3D image analysis and recognition. In: Proceeding sof the 11 th Scand inavian Conference on Image Analysis SCIA’99, DSAGM: 85–93.

  2. Cyganski D, Orr JA (1988) Object recognition and orientation determination by tensor methods. JAI Press 7(6):662–673

    Google Scholar 

  3. El Mallahi M, Mesbah A, Fadili H, Zenkouar K, Qjidaa H (2014) Compact Computation of Tchebichef Moments for 3D Object Representation, WSEAS Transactions on Circuits and Systems, ISSN / E-ISSN: 1109–2734 / 2224-266X, 13, 41: 368–380

  4. El Mallahi M, Mesbah A, El Fadili H, Zenkouar K, Qjidaa H (2015) Translation and scale invariants of three-dimensional Tchebichef moments, IEEE, Intelligent Systems and Computer Vision (ISCV), INSPEC Accession Number: 15141968, Print ISBN:978-1-4799-7510-5: 1-5

  5. Fehr J (2010) Local rotation invariant patch descriptors for 3D vector fields. In: Proceedings of the 20th International Conf Pattern Recognit ICPR’10, IEEE Computer Society: 1381–1384

  6. Fehr J, Burkhardt H (2008): 3D rotation invariant local binary patterns. In: Proceedings of The 19 th International Conf Pattern Recognit ICPR’08, IEEE Computer Society: 1–4

  7. Flusser J, Boldyš J, Zitová B (2003) Moment forms invariant to rotation and blur in arbitrary number of dimensions. IEEE Trans Pattern Anal Mach Intell 25:234–246

    Article  Google Scholar 

  8. Flusser J, T. Suk, B. Zitová (2009) Moments and moment invariants in pattern recognition, Wiley

  9. Galvez JM, Canton M (1993) Normalization and shape recognition of three-dimensional objects by 3D moments. Pattern Recogn 26(5):667–681

    Article  Google Scholar 

  10. Guo X (1993) Three dimensional moment invariants under rigid transformation. In: Proceedings of the Fifth International Conf Comput Anal Images Patterns (CAIP’93): 518–522

  11. Kakarala R, Mao D (2010) A theory of phase-sensitive rotation invariance with spherical harmonic and moment-based representations. In: IEEE Conf Comput Vis Pattern Recognit CVPR’10:105–112

  12. Kazhdan M (2007) An approximate and efficient method for optimal rotation alignment of 3D models. IEEE Trans Pattern Anal Mach Intell 29(7):1221–1229

    Article  MathSciNet  Google Scholar 

  13. Lo H, Don S (1989) 3-D moment forms: their construction and application to object identification and positioning. IEEE Trans Pattern Anal Mach Intell 11:1053–1064

    Article  Google Scholar 

  14. Mesbah A, EL Mallahi M and Qjidaa H (2016) An algorithm for fast computation of 3D Krawtchouk moments for volumetric image reconstruction, Springer, MedCT 2016 volume 1 ISBN: 978-3-319-30299-7 (print) 978-3-319-30301-7 (online), Lecture Notes in Electrical Engineering Volume 380

  15. Princeton, Princeton Shape Benchmark (2013) http://shape.cs.princeton.edu/benchmark/

  16. Reiss TH (1992) Features invariant to linear transformations in 2D and 3D. Proceedings of the 11th IAPR International Conference on Pattern Recognit., Conf C: Image, Speech Signal Anal, 3: 493–496

  17. Sadjadi FA, Hall EL (1980) Three-dimensionalm moment invariants. IEEE Trans Pattern Anal Mach Intell PAMI-2:127–136

    Article  MATH  Google Scholar 

  18. Skibbe H, Reisert M, Burkhardt H (2011) SHOG-spherical HOG descriptors for rotation invariant 3D object detection. In: Mester R, Felsberg M (Eds.), Deutsche Arbeitsgemeinschaft für Mustererkennung DAGM’11, Lecture Notes in Computer Science, vol. 6835, Springer: 142–15

  19. Suk T, Flusser J (2011) Tensor method for constructing 3D moment invariants. In: Proceedings of the 14th International Conf Comput Anal Images Patterns (CAIP’11), 2: 212–219

  20. Sun P (2015) Pathological brain detection based on wavelet entropy and Hu moment invariants. Biomed Mater Eng 26(S):1283–1290

    Google Scholar 

  21. Westenberg A, Roerdink JBTM, Wilkinson MHF (2007) Volumetric attribute filtering and interactive visualization using the max-tree representation. IEEE Trans Image Process 16:2943–2952

    Article  MathSciNet  Google Scholar 

  22. Xu D, Li H (2008) Geometric moment invariants. Pattern Recogn 41:240–249

    Article  MATH  Google Scholar 

  23. Yan C, Zhang Y, Dai F, Liang L (2013a) Efficient parallel framework for HEVC motion estimation on many-core processors, IEEE transactions on circuits and Systems for Video Technology. IEEE Trans Circuits Syst Video Technol 24(12):2077–2089

    Article  Google Scholar 

  24. Yan C, Zhang Y, Dai F, Liang L (2013b) Highly parallel framework for HEVC motion estimation on many-core platform, Data Compression Conference(DCC), 20–22 March 2013

  25. Yan C, Zhang Y, Xu J, Wu F (2014a) Highly parallel framework for HEVC coding unit partitioning tree decision on many-core processors, IEEE signal processing letters. IEEE Signal Processing Lett 21(5):573–576

    Article  Google Scholar 

  26. Yan C, Zhang Y, Dai F, Liang L (2014b) Parallel deblocking filter for HEVC on many-core processor. Electron Lett 50(5):367–368

    Article  Google Scholar 

  27. Yan C, Zhang Y, Dai F, Liang L (2014c) Efficient parallel HEVC intra prediction on many-core processor. Electron Lett 50(11):805–806

    Article  Google Scholar 

  28. Zhu H, Shu H, Zhou J, Luo L, Coatrieux JL (2007) Image analysis by discrete orthogonal Racah moments. Signal Process 87:687–708

    Article  MATH  Google Scholar 

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Correspondence to Mostafa El Mallahi.

Additional information

An erratum to this article is available at https://doi.org/10.1007/s11042-017-5048-4.

Appendices

Appendix 1

From Eq. 20, the radial Racah polynomials \( {\tilde{u}}_n^{\left(\alpha, \beta \right)}\left( r, a, b\right) \)can be expressed as a series of decreasing power of r as follows:

$$ \left(\begin{array}{c}\hfill {\tilde{u}}_0^{\left(\alpha, \beta \right)}\left( r, a, b\right)\hfill \\ {}\hfill {\tilde{u}}_1^{\left(\alpha, \beta \right)}\left( r, a, b\right)\hfill \\ {}\hfill \begin{array}{c}\hfill \vdots \hfill \\ {}\hfill {\tilde{u}}_n^{\left(\alpha, \beta \right)}\left( r, a, b\right)\hfill \end{array}\hfill \end{array}\right)=\left(\begin{array}{c}\hfill \begin{array}{c}\hfill {B}_{00}\kern0.5em \begin{array}{cc}\hfill \hfill & \hfill \hfill \end{array}\hfill \\ {}\hfill \begin{array}{cc}\hfill {B}_{10}\hfill & \hfill {B}_{11}\hfill \end{array}\begin{array}{cc}\hfill \hfill & \hfill \hfill \end{array}\hfill \\ {}\hfill \kern0.48em \begin{array}{cc}\hfill \vdots \hfill & \hfill \hfill \end{array}\begin{array}{cc}\hfill \vdots \hfill & \hfill \ddots \hfill \end{array}\hfill \end{array}\hfill \\ {}\hfill \begin{array}{cc}\hfill {B}_{n0}\hfill & \hfill {B}_{n1}\hfill \end{array}\begin{array}{cc}\hfill \cdots \hfill & \hfill {B}_{n n}\hfill \end{array}\hfill \end{array}\right)\left(\begin{array}{c}\hfill {r}^0\hfill \\ {}\hfill {r}^1\hfill \\ {}\hfill \begin{array}{c}\hfill \vdots \hfill \\ {}\hfill {r}^n\hfill \end{array}\hfill \end{array}\right) $$
(41)
$$ \begin{array}{l}\left(\begin{array}{c}\hfill {r}^0\hfill \\ {}\hfill {r}^1\hfill \\ {}\hfill \begin{array}{c}\hfill \vdots \hfill \\ {}\hfill {r}^n\hfill \end{array}\hfill \end{array}\right)={\left(\begin{array}{c}\hfill \begin{array}{c}\hfill \begin{array}{cc}\hfill {B}_{00}\hfill & \hfill \hfill \end{array}\begin{array}{cc}\hfill \hfill & \hfill \hfill \end{array}\hfill \\ {}\hfill \begin{array}{cc}\hfill {B}_{10}\hfill & \hfill {B}_{11}\hfill \end{array}\begin{array}{cc}\hfill \hfill & \hfill \hfill \end{array}\hfill \\ {}\hfill \kern0.48em \begin{array}{cc}\hfill \vdots \hfill & \hfill \hfill \end{array}\begin{array}{cc}\hfill \vdots \hfill & \hfill \ddots \hfill \end{array}\hfill \end{array}\hfill \\ {}\hfill \begin{array}{cc}\hfill {B}_{n0}\hfill & \hfill {B}_{n1}\hfill \end{array}\begin{array}{cc}\hfill \cdots \hfill & \hfill {B}_{n n}\hfill \end{array}\hfill \end{array}\right)}^{-1}\left(\begin{array}{c}\hfill {\tilde{u}}_0^{\left(\alpha, \beta \right)}\left( r, a, b\right)\hfill \\ {}\hfill {\tilde{u}}_1^{\left(\alpha, \beta \right)}\left( r, a, b\right)\hfill \\ {}\hfill \begin{array}{c}\hfill \vdots \hfill \\ {}\hfill {\tilde{u}}_n^{\left(\alpha, \beta \right)}\left( r, a, b\right)\hfill \end{array}\hfill \end{array}\right)\\ {}\ \begin{array}{cc}\hfill \hfill & \hfill \hfill \end{array}=\left(\begin{array}{c}\hfill \begin{array}{c}\hfill \begin{array}{cc}\hfill {D}_{00}\hfill & \hfill \hfill \end{array}\begin{array}{cc}\hfill \hfill & \hfill \hfill \end{array}\hfill \\ {}\hfill \begin{array}{cc}\hfill {D}_{10}\hfill & \hfill {D}_{11}\hfill \end{array}\begin{array}{cc}\hfill \hfill & \hfill \hfill \end{array}\hfill \\ {}\hfill \kern0.48em \begin{array}{cc}\hfill \vdots \hfill & \hfill \hfill \end{array}\begin{array}{cc}\hfill \vdots \hfill & \hfill \ddots \hfill \end{array}\hfill \end{array}\hfill \\ {}\hfill \begin{array}{cc}\hfill {D}_{n0}\hfill & \hfill {D}_{n1}\hfill \end{array}\begin{array}{cc}\hfill \cdots \hfill & \hfill {D}_{n n}\hfill \end{array}\hfill \end{array}\right)\left(\begin{array}{c}\hfill {\tilde{u}}_0^{\left(\alpha, \beta \right)}\left( r, a, b\right)\hfill \\ {}\hfill {\tilde{u}}_1^{\left(\alpha, \beta \right)}\left( r, a, b\right)\hfill \\ {}\hfill \begin{array}{c}\hfill \vdots \hfill \\ {}\hfill {\tilde{u}}_n^{\left(\alpha, \beta \right)}\left( r, a, b\right)\hfill \end{array}\hfill \end{array}\right)\end{array} $$
(42)

From Eq. 20, the radial Racah polynomials \( {\tilde{u}}_n^{\left(\alpha, \beta \right)}\left( r, a, b\right) \) can also be expressed as a series of decreasing power of xr as follows:

$$ \begin{array}{l}\left(\begin{array}{c}\hfill {\tilde{u}}_0^{\left(\alpha, \beta \right)}\left( r, a, b\right)\hfill \\ {}\hfill {\tilde{u}}_1^{\left(\alpha, \beta \right)}\left( r, a, b\right)\hfill \\ {}\hfill \begin{array}{c}\hfill \vdots \hfill \\ {}\hfill {\tilde{u}}_n^{\left(\alpha, \beta \right)}\left( r, a, b\right)\hfill \end{array}\hfill \end{array}\right)=\left(\begin{array}{c}\hfill \begin{array}{c}\hfill \begin{array}{cc}\hfill {B}_{00}\hfill & \hfill \hfill \end{array}\begin{array}{cc}\hfill \hfill & \hfill \hfill \end{array}\hfill \\ {}\hfill \begin{array}{cc}\hfill {B}_{10}\hfill & \hfill {B}_{11}\hfill \end{array}\begin{array}{cc}\hfill \hfill & \hfill \hfill \end{array}\hfill \\ {}\hfill \kern0.48em \begin{array}{cc}\hfill \vdots \hfill & \hfill \hfill \end{array}\begin{array}{cc}\hfill \vdots \hfill & \hfill \ddots \hfill \end{array}\hfill \end{array}\hfill \\ {}\hfill \begin{array}{cc}\hfill {B}_{n0}\hfill & \hfill {B}_{n1}\hfill \end{array}\begin{array}{cc}\hfill \cdots \hfill & \hfill {B}_{n n}\hfill \end{array}\hfill \end{array}\right)\left(\begin{array}{c}\hfill {(xr)}^0\hfill \\ {}\hfill {r}^1\hfill \\ {}\hfill \begin{array}{c}\hfill \vdots \hfill \\ {}\hfill {r}^n\hfill \end{array}\hfill \end{array}\right)\\ {}\begin{array}{cc}\hfill \begin{array}{cccc}\hfill \hfill & \hfill \hfill & \hfill \hfill & \hfill \hfill \end{array}\hfill & \hfill \hfill \end{array}=\left(\begin{array}{c}\hfill \begin{array}{c}\hfill \begin{array}{cc}\hfill {B}_{00}\hfill & \hfill \hfill \end{array}\begin{array}{cc}\hfill \hfill & \hfill \hfill \end{array}\hfill \\ {}\hfill \begin{array}{cc}\hfill {B}_{10}\hfill & \hfill {B}_{11}\hfill \end{array}\begin{array}{cc}\hfill \hfill & \hfill \hfill \end{array}\hfill \\ {}\hfill \kern0.48em \begin{array}{cc}\hfill \vdots \hfill & \hfill \hfill \end{array}\begin{array}{cc}\hfill \vdots \hfill & \hfill \ddots \hfill \end{array}\hfill \end{array}\hfill \\ {}\hfill \begin{array}{cc}\hfill {B}_{n0}\hfill & \hfill {B}_{n1}\hfill \end{array}\begin{array}{cc}\hfill \cdots \hfill & \hfill {B}_{n n}\hfill \end{array}\hfill \end{array}\right)\left(\begin{array}{c}\hfill \begin{array}{c}\hfill \begin{array}{cc}\hfill {x}^0\hfill & \hfill \hfill \end{array}\begin{array}{cc}\hfill \hfill & \hfill \hfill \end{array}\hfill \\ {}\hfill \begin{array}{cc}\hfill \hfill & \hfill {x}^1\hfill \end{array}\begin{array}{cc}\hfill \hfill & \hfill \hfill \end{array}\hfill \\ {}\hfill \begin{array}{cc}\hfill \hfill & \hfill \hfill \end{array}\begin{array}{cc}\hfill \hfill & \hfill \ddots \hfill \end{array}\hfill \end{array}\hfill \\ {}\hfill \begin{array}{cc}\hfill \hfill & \hfill \hfill \end{array}\begin{array}{cc}\hfill \hfill & \hfill {x}^n\hfill \end{array}\hfill \end{array}\right)\left(\begin{array}{c}\hfill \begin{array}{c}\hfill \begin{array}{cc}\hfill {D}_{00}\hfill & \hfill \hfill \end{array}\begin{array}{cc}\hfill \hfill & \hfill \hfill \end{array}\hfill \\ {}\hfill \begin{array}{cc}\hfill {D}_{10}\hfill & \hfill {D}_{11}\hfill \end{array}\begin{array}{cc}\hfill \hfill & \hfill \hfill \end{array}\hfill \\ {}\hfill \kern0.48em \begin{array}{cc}\hfill \vdots \hfill & \hfill \hfill \end{array}\begin{array}{cc}\hfill \vdots \hfill & \hfill \ddots \hfill \end{array}\hfill \end{array}\hfill \\ {}\hfill \begin{array}{cc}\hfill {D}_{n0}\hfill & \hfill {D}_{n1}\hfill \end{array}\begin{array}{cc}\hfill \cdots \hfill & \hfill {D}_{n n}\hfill \end{array}\hfill \end{array}\right)\left(\begin{array}{c}\hfill {\tilde{u}}_0^{\left(\alpha, \beta \right)}\left( r, a, b\right)\hfill \\ {}\hfill {\tilde{u}}_1^{\left(\alpha, \beta \right)}\left( r, a, b\right)\hfill \\ {}\hfill \begin{array}{c}\hfill \vdots \hfill \\ {}\hfill {\tilde{u}}_n^{\left(\alpha, \beta \right)}\left( r, a, b\right)\hfill \end{array}\hfill \end{array}\right)\\ {}\begin{array}{cc}\hfill \begin{array}{cccc}\hfill \hfill & \hfill \hfill & \hfill \hfill & \hfill \hfill \end{array}\hfill & \hfill \hfill \end{array}=\sum_{k=0}^n{\tilde{u}}_k^{\left(\alpha, \beta \right)}\left( r, a, b\right)\sum_{i= k}^n{x}^i{B}_{n i}{D}_{i k}\end{array} $$
(43)

Appendix 2

We can rewrite Eq. 32 in matrix from as

$$ \left(\begin{array}{c}\hfill {I}_{0 nml}^{sr}\hfill \\ {}\hfill {I}_{1 nml}^{sr}\hfill \\ {}\hfill \begin{array}{c}\hfill \begin{array}{c}\hfill \vdots \hfill \\ {}\hfill \begin{array}{c}\hfill \vdots \hfill \\ {}\hfill \vdots \hfill \end{array}\hfill \end{array}\hfill \\ {}\hfill {I}_{k nml}^{sr}\hfill \end{array}\hfill \end{array}\right)={e}^{jn \arg \left({R}_{0100}^{sr}\right)}{e}^{jm \arg \left({R}_{0010}^{sr}\right)}{e}^{jl \arg \left({R}_{0001}^{sr}\right)}\left(\begin{array}{c}\hfill \begin{array}{ccc}\hfill {\left({R}_{0000}^{sr}\right)}^{-1}\hfill & \hfill \hfill & \hfill \hfill \\ {}\hfill \hfill & \hfill {\left({R}_{0000}^{sr}\right)}^{-2}\hfill & \hfill \hfill \\ {}\hfill \vdots \hfill & \hfill \hfill & \hfill {\left({R}_{0000}^{sr}\right)}^{-\left( k+1\right)}\hfill \end{array}\hfill \\ {}\hfill \begin{array}{ccc}\hfill \hfill & \hfill \hfill & \hfill \hfill \end{array}\hfill \end{array}\right)\left(\begin{array}{c}\hfill \begin{array}{ccc}\hfill {B}_{00}\hfill & \hfill \hfill & \hfill \hfill \\ {}\hfill {B}_{10}\hfill & \hfill {B}_{11}\hfill & \hfill \hfill \\ {}\hfill \vdots \hfill & \hfill \ddots \hfill & \hfill \hfill \end{array}\hfill \\ {}\hfill \begin{array}{ccc}\hfill {B}_{k0}\hfill & \hfill {B}_{k1}\hfill & \hfill {B}_{k k}\hfill \end{array}\hfill \end{array}\right)\left(\begin{array}{c}\hfill \begin{array}{ccc}\hfill {D}_{00}\hfill & \hfill \hfill & \hfill \hfill \\ {}\hfill {D}_{10}\hfill & \hfill {D}_{11}\hfill & \hfill \hfill \\ {}\hfill \vdots \hfill & \hfill \ddots \hfill & \hfill \hfill \end{array}\hfill \\ {}\hfill \begin{array}{ccc}\hfill {D}_{k0}\hfill & \hfill \hfill & \hfill {D}_{k k}\hfill \end{array}\hfill \end{array}\right)\left(\begin{array}{c}\hfill {R}_{0 nml}^{sr}\hfill \\ {}\hfill {R}_{1 nml}^{sr}\hfill \\ {}\hfill \begin{array}{c}\hfill \begin{array}{c}\hfill \vdots \hfill \\ {}\hfill \begin{array}{c}\hfill \vdots \hfill \\ {}\hfill \vdots \hfill \end{array}\hfill \end{array}\hfill \\ {}\hfill {R}_{k nml}^{sr}\hfill \end{array}\hfill \end{array}\right) $$
(44)

From Eq. 32 we can also get

$$ \arg \left({R}_{0100}^{sr}\right)= \arg \left({R}_{0100}\right)+{\theta}^{\hbox{'}}, \arg \left({R}_{0010}^{sr}\right)= \arg \left({R}_{0010}\right)+{\varphi^{\hbox{'}}}_{,}, \arg \left({SR}_{0001}^{sr}\right)= \arg \left({R}_{0001}\right)+{\psi}^{\hbox{'}},\mathrm{and}\kern0.37em {R}_{0000}^{sr}={\lambda}^2{R}_{0100} $$
(45)

Similarly Eq. 31 can also be written in the matrix form as

$$ \left(\begin{array}{c}\hfill {R}_{0 nml}^{sr}\hfill \\ {}\hfill {R}_{1 nml}^{sr}\hfill \\ {}\hfill \begin{array}{c}\hfill \begin{array}{c}\hfill \vdots \hfill \\ {}\hfill \begin{array}{c}\hfill \vdots \hfill \\ {}\hfill \vdots \hfill \end{array}\hfill \end{array}\hfill \\ {}\hfill {R}_{k nml}^{sr}\hfill \end{array}\hfill \end{array}\right)={e}^{{jn\theta}^{\hbox{'}}}{e}^{{jm\varphi}^{\hbox{'}}}{e}^{{jl\psi}^{\hbox{'}}}\left(\begin{array}{c}\hfill \begin{array}{ccc}\hfill {B}_{00}\hfill & \hfill \hfill & \hfill \hfill \\ {}\hfill {B}_{10}\hfill & \hfill {B}_{11}\hfill & \hfill \hfill \\ {}\hfill \vdots \hfill & \hfill \ddots \hfill & \hfill \hfill \end{array}\hfill \\ {}\hfill \begin{array}{ccc}\hfill {B}_{k0}\hfill & \hfill {B}_{k1}\hfill & \hfill {B}_{k k}\hfill \end{array}\hfill \end{array}\right)\left(\begin{array}{c}\hfill \begin{array}{ccc}\hfill {D}_{00}\hfill & \hfill \hfill & \hfill \hfill \\ {}\hfill {D}_{10}\hfill & \hfill {D}_{11}\hfill & \hfill \hfill \\ {}\hfill \vdots \hfill & \hfill \ddots \hfill & \hfill \hfill \end{array}\hfill \\ {}\hfill \begin{array}{ccc}\hfill {D}_{k0}\hfill & \hfill \hfill & \hfill {D}_{k k}\hfill \end{array}\hfill \end{array}\right)\left(\begin{array}{c}\hfill {R}_{0 nml}\hfill \\ {}\hfill {R}_{1 nml}\hfill \\ {}\hfill \begin{array}{c}\hfill \begin{array}{c}\hfill \vdots \hfill \\ {}\hfill \begin{array}{c}\hfill \vdots \hfill \\ {}\hfill \vdots \hfill \end{array}\hfill \end{array}\hfill \\ {}\hfill {R}_{k nml}\hfill \end{array}\hfill \end{array}\right) $$
(46)

By substituting Eqs. 46 and 45 into Eq. 44, we get

$$ \begin{array}{l}\left(\begin{array}{c}\hfill {I}_{0 nml}^{sr}\hfill \\ {}\hfill {I}_{1 nml}^{sr}\hfill \\ {}\hfill \begin{array}{c}\hfill \begin{array}{c}\hfill \vdots \hfill \\ {}\hfill \begin{array}{c}\hfill \vdots \hfill \\ {}\hfill \vdots \hfill \end{array}\hfill \end{array}\hfill \\ {}\hfill {I}_{k nml}^{sr}\hfill \end{array}\hfill \end{array}\right)={e}^{jn \arg \left({R}_{0100}\right)}{e}^{jm \arg \left({R}_{0010}\right)}{e}^{jl \arg \left({R}_{0001}\right)}\left(\begin{array}{c}\hfill \begin{array}{ccc}\hfill {B}_{00}\hfill & \hfill \hfill & \hfill \hfill \\ {}\hfill {B}_{10}\hfill & \hfill {B}_{11}\hfill & \hfill \hfill \\ {}\hfill \vdots \hfill & \hfill \ddots \hfill & \hfill \hfill \end{array}\hfill \\ {}\hfill \begin{array}{ccc}\hfill {B}_{k0}\hfill & \hfill {B}_{k1}\hfill & \hfill {B}_{k k}\hfill \end{array}\hfill \end{array}\right)\left(\begin{array}{c}\hfill \begin{array}{ccc}\hfill {R_{0000}}^{-1}\hfill & \hfill \hfill & \hfill \hfill \\ {}\hfill \hfill & \hfill {R_{0000}}^{-2}\hfill & \hfill \hfill \\ {}\hfill \vdots \hfill & \hfill \hfill & \hfill {R_{0000}}^{-\left( k+1\right)}\hfill \end{array}\hfill \\ {}\hfill \begin{array}{ccc}\hfill \hfill & \hfill \hfill & \hfill \hfill \end{array}\hfill \end{array}\right)\\ {}\times \left(\begin{array}{c}\hfill \begin{array}{ccc}\hfill {x}^{-1}\hfill & \hfill \hfill & \hfill \hfill \\ {}\hfill \hfill & \hfill {x}^{-2}\hfill & \hfill \hfill \\ {}\hfill \vdots \hfill & \hfill \hfill & \hfill \hfill \end{array}\hfill \\ {}\hfill \begin{array}{ccc}\hfill \hfill & \hfill \hfill & \hfill {x}^{-\left( k+1\right)}\hfill \end{array}\hfill \end{array}\right)\left(\begin{array}{c}\hfill \begin{array}{ccc}\hfill {D}_{00}\hfill & \hfill \hfill & \hfill \hfill \\ {}\hfill {D}_{10}\hfill & \hfill {D}_{11}\hfill & \hfill \hfill \\ {}\hfill \vdots \hfill & \hfill \ddots \hfill & \hfill \hfill \end{array}\hfill \\ {}\hfill \begin{array}{ccc}\hfill {D}_{k0}\hfill & \hfill \hfill & \hfill {D}_{k k}\hfill \end{array}\hfill \end{array}\right)\ \left(\begin{array}{c}\hfill \begin{array}{ccc}\hfill {B}_{00}\hfill & \hfill \hfill & \hfill \hfill \\ {}\hfill {B}_{10}\hfill & \hfill {B}_{11}\hfill & \hfill \hfill \\ {}\hfill \vdots \hfill & \hfill \ddots \hfill & \hfill \hfill \end{array}\hfill \\ {}\hfill \begin{array}{ccc}\hfill {B}_{k0}\hfill & \hfill {B}_{k1}\hfill & \hfill {B}_{k k}\hfill \end{array}\hfill \end{array}\right)\left(\begin{array}{c}\hfill \begin{array}{ccc}\hfill {x}^1\hfill & \hfill \hfill & \hfill \hfill \\ {}\hfill \hfill & \hfill {x}^2\hfill & \hfill \hfill \\ {}\hfill \vdots \hfill & \hfill \hfill & \hfill \hfill \end{array}\hfill \\ {}\hfill \begin{array}{ccc}\hfill \hfill & \hfill \hfill & \hfill {x}^{k+1}\hfill \end{array}\hfill \end{array}\right)\ \left(\begin{array}{c}\hfill \begin{array}{ccc}\hfill {D}_{00}\hfill & \hfill \hfill & \hfill \hfill \\ {}\hfill {D}_{10}\hfill & \hfill {D}_{11}\hfill & \hfill \hfill \\ {}\hfill \vdots \hfill & \hfill \ddots \hfill & \hfill \hfill \end{array}\hfill \\ {}\hfill \begin{array}{ccc}\hfill {D}_{k0}\hfill & \hfill \hfill & \hfill {D}_{k k}\hfill \end{array}\hfill \end{array}\right)\left(\begin{array}{c}\hfill {R}_{0 nml}\hfill \\ {}\hfill {R}_{1 nml}^{sr}\hfill \\ {}\hfill \begin{array}{c}\hfill \begin{array}{c}\hfill \vdots \hfill \\ {}\hfill \begin{array}{c}\hfill \vdots \hfill \\ {}\hfill \vdots \hfill \end{array}\hfill \end{array}\hfill \\ {}\hfill {R}_{k nml}\hfill \end{array}\hfill \end{array}\right)\end{array} $$
(47)

Science

$$ \left(\begin{array}{c}\hfill \begin{array}{ccc}\hfill {B}_{00}\hfill & \hfill \hfill & \hfill \hfill \\ {}\hfill {B}_{10}\hfill & \hfill {B}_{11}\hfill & \hfill \hfill \\ {}\hfill \vdots \hfill & \hfill \ddots \hfill & \hfill \hfill \end{array}\hfill \\ {}\hfill \begin{array}{ccc}\hfill {B}_{k0}\hfill & \hfill {B}_{k1}\hfill & \hfill {B}_{k k}\hfill \end{array}\hfill \end{array}\right)\left(\begin{array}{c}\hfill \begin{array}{ccc}\hfill {D}_{00}\hfill & \hfill \hfill & \hfill \hfill \\ {}\hfill {D}_{10}\hfill & \hfill {D}_{11}\hfill & \hfill \hfill \\ {}\hfill \vdots \hfill & \hfill \ddots \hfill & \hfill \hfill \end{array}\hfill \\ {}\hfill \begin{array}{ccc}\hfill {D}_{k0}\hfill & \hfill \hfill & \hfill {D}_{k k}\hfill \end{array}\hfill \end{array}\right)=\left(\begin{array}{c}\hfill \begin{array}{ccc}\hfill 1\hfill & \hfill \hfill & \hfill \hfill \\ {}\hfill \hfill & \hfill 1\hfill & \hfill \hfill \\ {}\hfill \vdots \hfill & \hfill \ddots \hfill & \hfill \hfill \end{array}\hfill \\ {}\hfill \begin{array}{ccc}\hfill \hfill & \hfill \hfill & \hfill 1\hfill \end{array}\hfill \end{array}\right)\left(\begin{array}{c}\hfill \begin{array}{ccc}\hfill {x}^{-1}\hfill & \hfill \hfill & \hfill \hfill \\ {}\hfill \hfill & \hfill {x}^{-2}\hfill & \hfill \hfill \\ {}\hfill \vdots \hfill & \hfill \hfill & \hfill \hfill \end{array}\hfill \\ {}\hfill \begin{array}{ccc}\hfill \hfill & \hfill \hfill & \hfill {x}^{-\left( k+1\right)}\hfill \end{array}\hfill \end{array}\right)\left(\begin{array}{c}\hfill \begin{array}{ccc}\hfill {x}^1\hfill & \hfill \hfill & \hfill \hfill \\ {}\hfill \hfill & \hfill {x}^2\hfill & \hfill \hfill \\ {}\hfill \vdots \hfill & \hfill \hfill & \hfill \hfill \end{array}\hfill \\ {}\hfill \begin{array}{ccc}\hfill \hfill & \hfill \hfill & \hfill {x}^{k+1}\hfill \end{array}\hfill \end{array}\right)=\left(\begin{array}{c}\hfill \begin{array}{ccc}\hfill 1\hfill & \hfill \hfill & \hfill \hfill \\ {}\hfill \hfill & \hfill 1\hfill & \hfill \hfill \\ {}\hfill \vdots \hfill & \hfill \ddots \hfill & \hfill \hfill \end{array}\hfill \\ {}\hfill \begin{array}{ccc}\hfill \hfill & \hfill \hfill & \hfill 1\hfill \end{array}\hfill \end{array}\right) $$

Eq. 47 can be rewritten as

$$ \begin{array}{l}\left(\begin{array}{c}\hfill {I}_{0 nml}^{sr}\hfill \\ {}\hfill {I}_{1 nml}^{sr}\hfill \\ {}\hfill \begin{array}{c}\hfill \begin{array}{c}\hfill \vdots \hfill \\ {}\hfill \begin{array}{c}\hfill \vdots \hfill \\ {}\hfill \vdots \hfill \end{array}\hfill \end{array}\hfill \\ {}\hfill {I}_{k nml}^{sr}\hfill \end{array}\hfill \end{array}\right)={e}^{jn \arg \left({R}_{0100}\right)}{e}^{jm \arg \left({R}_{0010}\right)}{e}^{jl \arg \left({R}_{0001}\right)}\left(\begin{array}{c}\hfill \begin{array}{ccc}\hfill {B}_{00}\hfill & \hfill \hfill & \hfill \hfill \\ {}\hfill {B}_{10}\hfill & \hfill {B}_{11}\hfill & \hfill \hfill \\ {}\hfill \vdots \hfill & \hfill \ddots \hfill & \hfill \hfill \end{array}\hfill \\ {}\hfill \begin{array}{ccc}\hfill {B}_{k0}\hfill & \hfill {B}_{k1}\hfill & \hfill {B}_{k k}\hfill \end{array}\hfill \end{array}\right)\left(\begin{array}{c}\hfill \begin{array}{ccc}\hfill {R_{0000}}^{-1}\hfill & \hfill \hfill & \hfill \hfill \\ {}\hfill \hfill & \hfill {R_{0000}}^{-2}\hfill & \hfill \hfill \\ {}\hfill \vdots \hfill & \hfill \hfill & \hfill {R_{0000}}^{-\left( k+1\right)}\hfill \end{array}\hfill \\ {}\hfill \begin{array}{ccc}\hfill \hfill & \hfill \hfill & \hfill \hfill \end{array}\hfill \end{array}\right)\left(\begin{array}{c}\hfill \begin{array}{ccc}\hfill {D}_{00}\hfill & \hfill \hfill & \hfill \hfill \\ {}\hfill {D}_{10}\hfill & \hfill {D}_{11}\hfill & \hfill \hfill \\ {}\hfill \vdots \hfill & \hfill \ddots \hfill & \hfill \hfill \end{array}\hfill \\ {}\hfill \begin{array}{ccc}\hfill {D}_{k0}\hfill & \hfill \hfill & \hfill {D}_{k k}\hfill \end{array}\hfill \end{array}\right)\left(\begin{array}{c}\hfill {R}_{0 nml}\hfill \\ {}\hfill {R}_{1 nml}^{sr}\hfill \\ {}\hfill \begin{array}{c}\hfill \begin{array}{c}\hfill \vdots \hfill \\ {}\hfill \begin{array}{c}\hfill \vdots \hfill \\ {}\hfill \vdots \hfill \end{array}\hfill \end{array}\hfill \\ {}\hfill {R}_{k nml}\hfill \end{array}\hfill \end{array}\right)\\ {}\ \begin{array}{ccc}\hfill \hfill & \hfill \hfill & \hfill =\left(\begin{array}{c}\hfill {I}_{0 nml}\hfill \\ {}\hfill {I}_{1 nml}\hfill \\ {}\hfill \begin{array}{c}\hfill \begin{array}{c}\hfill \vdots \hfill \\ {}\hfill \begin{array}{c}\hfill \vdots \hfill \\ {}\hfill \vdots \hfill \end{array}\hfill \end{array}\hfill \\ {}\hfill {I}_{k nml}\hfill \end{array}\hfill \end{array}\right)\hfill \end{array}\end{array} $$

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El Mallahi, M., Zouhri, A., Mesbah, A. et al. Radial invariant of 2D and 3D Racah moments. Multimed Tools Appl 77, 6583–6604 (2018). https://doi.org/10.1007/s11042-017-4573-5

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