A novel method for invariant image reconstruction

• Autorzy: Pawlak Mirosław , Panesar Gurmukh Singh , Korytkowski Marcin

Identyfikatory

DOI

10.2478/jaiscr-2021-0005

• Języki publikacji: EN

Abstrakty

EN

In this paper we propose a novel method for invariant image reconstruction with the properly selected degree of symmetry. We make use of Zernike radial moments to represent an image due to their invariance properties to isometry transformations and the ability to uniquely represent the salient features of the image. The regularized ridge regression estimation strategy under symmetry constraints for estimating Zernike moments is proposed. This extended regularization problem allows us to enforces the bilateral symmetry in the reconstructed object. This is achieved by the proper choice of two regularization parameters controlling the level of reconstruction accuracy and the acceptable degree of symmetry. As a byproduct of our studies we propose an algorithm for estimating an angle of the symmetry axis which in turn is used to determine the possible asymmetry present in the image. The proposed image recovery under the symmetry constraints model is tested in a number of experiments involving image reconstruction and symmetry estimation.

Słowa kluczowe

EN

object representation; invariant features; symmetry; radial orthogonal moments; continuous symmetry; ridge regression

• Wydawca: University of Social Sciences
• Czasopismo: Journal of Artificial Intelligence and Soft Computing Research
• Rocznik: 2021
• Tom: Vol. 11, No. 1
• Strony: 69--80
• Opis fizyczny: Bib liogr. 13 poz., rys.

Twórcy

autor

Pawlak Mirosław

• Department of Electrical and Computer Engineering, University of Manitoba, Canada
• Information Technology Institute, University of Social Sciences, Lodz, Poland

autor

Panesar Gurmukh Singh

• Department of Electrical and Computer Engineering, University of Manitoba, Canada

autor

Korytkowski Marcin

• Institute of Computational Intelligence, Czestochowa University of Technology, Czestochowa, Poland

Bibliografia

• [1] U. Grenander, Elements of Pattern Theory. John Hopkins University Press, 1996.
• [2] D. Zhang and G. Lu, Review of shape representation and description techniques, Pattern Recognition, vol. 37, pp. 1–19, 2004.
• [3] H. Weyl, Symmetry. Princeton University Press, 1952.
• [4] J. Rosen, Symmetry in Science: An Introduction to the General Theory. Springer-Verlag, 1995.
• [5] H. Zabrodsky, S. Peleg, and D. Avnir, Symmetry as a continuous feature, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 17, pp. 1154–1166, 1995.
• [6] N. Bissantz, H. Holzmann, and M. Pawlak, Improving PSF calibration in confocal microscopic imaging-estimating and exploiting bilateral symmetry, The Annals of Applied Statistics, vol. 4, pp. 1871–1891, 2010.
• [7] J. Flusser, T. Suk, and B. Zitova, 2D and 3D Image Analysis by Moments. John Wiley and Sons, 2017.
• [8] M. Pawlak, Image Analysis by Moments. Publishing House of Technical University of Wroclaw, 2006.
• [9] A. B. Bhatia and E. Wolf, On the circle polynomials of Zernike and related orthogonal sets, Proceedings of Cambridge Philosophical Society, vol. 50, pp. 40–48, 1954.
• [10] N. Bissantz, H. Holzmann, and M. Pawlak, Testing for image symmetries-with application to confocal microscopy, IEEE Transactions on Information Theory, vol. 55, pp. 1841–1855, 2009.
• [11] Y. Xin, M. Pawlak, and S. Liao, Accurate computation of Zernike moments in polar coordinates, IEEE Transactions on Image Processing, vol. 16, pp. 581–587, 2007.
• [12] M. Pawlak and S. Liao, On the recovery of a function on a circular domain, IEEE Transactions on Information Theory, vol. 48, pp. 2736–2753, 2002.
• [13] G. James, D. Witten, T. Hastie, and R. Tibshirani, An Introduction to Statistical Learning. Springer, 2013.

Uwagi

Opracowanie rekordu ze środków MNiSW, umowa Nr 461252 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2021).