[Campisi, P., Neri, A., Panci, G. and Scarano, G. (2004). Robust rotation-invariant texture classification using a model based approach, IEEE Transactions on Image Processing13(6): 782–791.10.1109/TIP.2003.82260715648869]Search in Google Scholar
[Dai, X., Shu, H., Luo, L., Han, G.N. and Coatrieux, J.L. (2010). Reconstruction of tomographic images from limited range projections using discrete Radon transform and Tchebichef moments, Pattern Recognition43(3): 1152–1164.10.1016/j.patcog.2009.07.009]Search in Google Scholar
[Dunkl, C.F. and Xu, Y. (2001). Orthogonal Polynomials of Several Variables, Cambridge University Press, Cambridge.10.1017/CBO9780511565717]Search in Google Scholar
[Fujarewicz, K. (2010). Planning identification experiments for cell signaling pathways: An NFκB case study, International Journal of Applied Mathematics and Computer Science20(4): 773–780, DOI: 10.2478/v10006-010-0059-6.10.2478/v10006-010-0059-6]Search in Google Scholar
[Hu, M. (1962). Visual pattern recognition by moment invariants, IRE Transactions on Information Theory8(2): 179–187.10.1109/TIT.1962.1057692]Search in Google Scholar
[Iliev, P. and Xu, Y. (2007). Discrete orthogonal polynomials and difference equations of several variables, Advances in Mathematics212(1): 1–36.10.1016/j.aim.2006.09.012]Search in Google Scholar
[Ismail, M., Foncannon, J. and Pekonen, O. (2008). Classical and quantum orthogonal polynomials in one variable, The Mathematical Intelligencer30(1): 54–60.10.1007/BF02985757]Search in Google Scholar
[Mukundan, R., Ong, S. and Lee, P.A. (2001). Image analysis by Tchebichef moments, IEEE Transactions on Image Processing10(9): 1357–1364.10.1109/83.94185918255550]Search in Google Scholar
[Nene, S., Nayar, S. and Murase, H. (1988). Columbia Object Image Library (coil 100) 1996, Ph.D. thesis, Columbia University, New York, NY.]Search in Google Scholar
[Papakostas, G., Karakasis, E. and Koulouriotis, D. (2010). Novel moment invariants for improved classification performance in computer vision applications, Pattern Recognition43(1): 58–68.10.1016/j.patcog.2009.05.008]Search in Google Scholar
[See, K., Loke, K., Lee, P. and Loe, K. (2007). Image reconstruction using various discrete orthogonal polynomials in comparison with DCT, Applied Mathematics and Computation193(2): 346–359.10.1016/j.amc.2007.03.080]Search in Google Scholar
[Sroubek, F., Cristóbal, G. and Flusser, J. (2007). A unified approach to superresolution and multichannel blind deconvolution, IEEE Transactions on Image Processing16(9): 2322–2332.10.1109/TIP.2007.90325617784605]Search in Google Scholar
[Teague, M.R. (1980). Image analysis via the general theory of moments, Journal of the Optical Society of America A70(8): 920–930.10.1364/JOSA.70.000920]Search in Google Scholar
[Wang, J.Z., Wiederhold, G., Firschein, O. and Wei, S.X. (1997). Wavelet-based image indexing techniques with partial sketch retrieval capability, Proceedings of the IEEE International Forum on Research and Technology Advances in Digital Libraries, ADL 1997, Washington, DC, USA, pp. 13–24.]Search in Google Scholar
[Wang, Z. and Bovik, A.C. (2009). Mean squared error: Love it or leave it? A new look at signal fidelity measures, IEEE Signal Processing Magazine26(1): 98–117.10.1109/MSP.2008.930649]Search in Google Scholar
[Wang, Z., Bovik, A.C., Sheikh, H.R. and Simoncelli, E.P. (2004). Image quality assessment: From error visibility to structural similarity, IEEE Transactions on Image Processing13(4): 600–612.10.1109/TIP.2003.819861]Search in Google Scholar
[Hunek, W.P and Latawiec, K.J. (2011). A study on new right/left inverses of nonsquare polynomial matrices, International Journal of Applied Mathematics and Computer Science21(2): 331–348, DOI: 10.2478/v10006-011-0025-y.10.2478/v10006-011-0025-y]Search in Google Scholar
[Xu, Y. (2004). On discrete orthogonal polynomials of several variables, Advances in Applied Mathematics33(3): 615–632.10.1016/j.aam.2004.03.002]Search in Google Scholar
[Xu, Y. (2005). Second-order difference equations and discrete orthogonal polynomials of two variables, International Mathematics Research Notices2005(8): 449–475.]Search in Google Scholar
[Yap, P.T., Paramesran, R. and Ong, S.H. (2003). Image analysis by Krawtchouk moments, IEEE Transactions on Image Processing12(11): 1367–1377.10.1109/TIP.2003.81801918244694]Search in Google Scholar
[Yap, P. T., Paramesran, R. and Ong, S. H. (2007). Image analysis using Hahn moments, IEEE Transactions on Pattern Analysis and Machine Intelligence29(11): 2057–2062.10.1109/TPAMI.2007.7070917848784]Search in Google Scholar
[Zhang, D. and Lu, G. (2001). Content-based shape retrieval using different shape descriptors: A comparative study, Proceedings of the International Conference on Intelligent Multimedia and Distance Education, ICIMADE01, Fargo, ND, USA, pp. 1–9.]Search in Google Scholar
[Zhou, J., Shu, H., Zhu, H., Toumoulin, C. and Luo, L. (2005). Image analysis by discrete orthogonal Hahn moments, in J.S. Marques, N. P´erez de la Blanca and P. Pina (Eds.), Image Analysis and Recognition, Springer, Berlin/Heidelberg, pp. 524–531.10.1007/11559573_65]Search in Google Scholar
[Zhu, H. (2012). Image representation using separable two-dimensional continuous and discrete orthogonal moments, Pattern Recognition45(4): 1540–1558.10.1016/j.patcog.2011.10.002]Search in Google Scholar
[Zhu, H., Liu, M., Li, Y., Shu, H. and Zhang, H. (2011). Image description with nonseparable two-dimensional Charlier and Meixner moments, International Journal of Pattern Recognition and Artificial Intelligence25(1): 37–55.10.1142/S0218001411008506]Search in Google Scholar
[Zhu, H., Liu, M., Shu, H., Zhang, H. and Luo, L. (2010). General form for obtaining discrete orthogonal moments, IET Image Processing4(5): 335–352.10.1049/iet-ipr.2009.0195]Search in Google Scholar
[Zhu, H., Shu, H., Zhou, J., Luo, L. and Coatrieux, J.L. (2007). Image analysis by discrete orthogonal dual Hahn moments, Pattern Recognition Letters28(13): 1688–1704.10.1016/j.patrec.2007.04.013]Search in Google Scholar
[Zunić, J., Hirota, K. and Rosin, P.L. (2010). A Hu moment invariant as a shape circularity measure, Pattern Recognition43(1): 47–57.10.1016/j.patcog.2009.06.017]Search in Google Scholar