Abstract
A novel kernel-based method is proposed for fast, highly accurate and numerically stable computations of polar harmonic transforms (PHT) in polar coordinates. Euler formula is used to derive a novel trigonometric formula where the later one is used in the kernel generation. The simplified radial and angular kernels are used in efficient computation PHTs. The proposed method removes the numerical approximation errors involved in conventional methods and provides highly accurate PHTs coefficients which results in highly improved image reconstruction capabilities. Numerical experiments are performed where the results are compared with those of the recent existing methods. In addition to the tremendous reduction in computational times, the obtained results of the proposed method clearly show a significant improvement in rotational invariance.















Similar content being viewed by others
References
Yap, P.T., Jiang, X., Kot, A.C.: Two dimensional polar harmonic transforms for invariant image representation. IEEE Trans. Pattern Anal. Mach. Intell. 32, 1259–1270 (2010)
Teague, M.R.: Image analysis via the general theory of moments. J. Opt. Soc. Am. 70, 920–930 (1980)
Teh, C.-H., Chin, R.T.: On image analysis by the methods of moments. IEEE Trans. Pattern Anal. Mach. Intell. 10(4), 496–513 (1988)
Sheng, Y., Shen, L.: Orthogonal Fourier-Mellin moments for invariant pattern recognition. J. Opt. Soc. Am. A 11, 1748–1757 (1994)
Hoang, T.V., Tabbone, S.: Generic polar harmonic transforms for invariant image representation. Image Vis. Comput. 32, 497–506 (2014)
Liu, M., Jiang, X., Kot, A.C., Yap, P.T.: Application of polar harmonic transforms to fingerprint classification. In: Chen, C.H. (ed.) Emerging Topics in Computer Vision and its Applications. World Scientific Publishing, Singapore (2011)
Miao, Q., Liu, J., Li, W., Shi, J., Wang, Y.: Three novel invariant moments based on radon and polar harmonic transform. Opt. Commun. 285, 1044–1048 (2012)
Li, Y.N.: Robust image hash function based on polar harmonic transforms and feature selection. In: 2012 Eighth IEEE international conference on computational intelligence and security, pp. 420–423
Li, L., Li, S., Wang, J.: Copy-move forgery detection based on PHT. In: Proceedings of the world congress on information and communication technologies (WICT’12), pp. 1061–1065, IEEE, November 2012
Li, Yuenan: Image copy-move forgery detection based on polar cosine transform and approximate nearest neighbor searching. Forensic Sci. 224(1–3), 59–67 (2013)
Li, L., Li, S., Abraham, A., Pan, J.S.: Geometrically invariant image watermarking using Polar Harmonic Transforms. Inf. Sci. 199, 1–19 (2012)
Tsougenis, E.D., Papakostas, G.A., Koulouriotis, D.E., Tourassis, V.D.: Towards adaptively of image watermarking in polar harmonic transforms domain. Opt. Laser Technol. 54, 84–97 (2013)
Singh, C., Ranade, S.K.: Rotation invariant moments and transforms for geo-metrically invariant image watermarking. J. Electron. Imaging 22(1), 013–034 (2013)
Min, Q., Bing-Zhao, L., Huafei, S.: Image watermarking using polar harmonic transform with parameters SL. Signal Process. Image Commun. (2015)
Yang, Z., Kamata, S.: Fast Polar Harmonic Transforms. In: Proceedings of 11th International Conference Control, Automation, Robotics and Vision, Singapore, pp. 673–676, 7–10th Dec 2010
Yang, Z., Kamata, S.: Fast Polar Cosine Transform for image description. In: IAPR conference on machine vision applications, June 13–15, Nara, Japan (2011)
Hoang, Thai V., Tabbone, Salvatore: Fast generic polar harmonic transforms. IEEE Trans. Image Process. 23(7), 2961–2970 (2014)
Liao, S.X., Pawlak, M.: On the accuracy of Zernike moments for image analysis. IEEE Trans. Pattern Anal. Mach. Intell. 20(12), 1358–1364 (1998)
Singh, C., Upneja, R.: Accuracy and numerical stability of high-order polar harmonic transforms. IET Image Proc. 6(6), 617–626 (2012)
Singh, C., Kaur, A.: Fast computation of polar harmonic transforms. J. Real-Time Image Proc. 10(1), 50–66 (2015)
Xin, Y., Pawlak, M., Liao, S.: Accurate computation of Zernike moments in polar coordinates. IEEE Trans. Image Process. 16(2), 581–587 (2007)
Hosny, K.M., Shouman, M.A., Abdel-Salam, H.M.: Fast computation of orthogonal Fourier-Mellin moments in polar coordinates. J. Real-Time Image Process. 6(2), 73–80 (2011)
Harris, J.W., Stocker, H.: Handbook of Mathematics and Computational Sciences. Springer, New York (1998)
Hosny, K.M.: Accurate orthogonal circular moment invariants of gray-level images. J. Comput. Sci. 7(5), 715–722 (2011)
Liu, C., Huang, X.-H., Wang, M.: Fast computation of Zernike moments in polar coordinates. IET Image Proc. 6(7), 996–1004 (2012)
Singh, C., Walia, E.: Computation of Zernike moments in improved polar configuration. IET Image Proc. 3(4), 217–227 (2009)
Hosny, K.M.: Fast computation of accurate Zernike moments. J. Real-Time Image Process. 3(1), 97–107 (2008)
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Hosny, K.M., Darwish, M.M. A kernel-based method for fast and accurate computation of PHT in polar coordinates. J Real-Time Image Proc 16, 1235–1247 (2019). https://doi.org/10.1007/s11554-016-0622-y
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11554-016-0622-y