Abstract
Digital image watermarking is an effective image copyright protection technology, which embeds the copyright information into the image to be protected, therefore achieving the purpose of image copyright protection. The recently proposed Polar harmonic transforms (PHTs) have provided a set of powerful tools for image representation. However, the accuracy of PHTs suffers from various errors, such as the geometric and numerical integration errors. In this paper, we propose an accurate computational framework of PHTs based on wavelet integration approach and present a novel accurate PHT-based multiplicative watermarking algorithm. We embed watermark data into selected blocks of the host image by modifying the PHT magnitudes due to strong robustness against various attacks. At the receiver, the distribution of watermarked noisy PHT magnitudes is analytically calculated; closed form expressions are obtained for extracting the watermark bits. Compared with other decoders, the proposed decoder has better performance in terms of watermark robustness. In addition, the proposed watermarking algorithm can effectively resist geometrical attacks and common image processing attacks.
Keywords
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsReferences
Bao, P., Ma, X.H.: Image adaptive watermarking using wavelet domain singular value decomposition. IEEE Trans. Circuits Syst. Video Technol. 15(1), 96–102 (2005)
Liu, X.L., Han, G.N.: Fractional Krawtchouk transform with an application to image watermarking. IEEE Trans. Signal Process. 65(7), 1894–1908 (2017)
Dong, L., Yan, Q., Lv, Y., Deng, S.: Full band watermarking in DCT domain with Weibull model. Multimedia Tools Appl. 76(2), 1983–2000 (2016). https://doi.org/10.1007/s11042-015-3115-2
Qin, C., Chang, C.C.: A novel joint data-hiding and compression scheme based on SMVQ and image inpainting. IEEE Trans. Image Process. 23(3), 969–978 (2014)
Qin, C., Zhang, X.Z.: Effective reversible data hiding in encrypted image with privacy protection for image content. J. Vis. Commun. Image Represent. 31(C), 154–164 (2015)
Makbol, N.M., Khoo, B.E., Rassem, T.H.: Block-based discrete wavelet transform-singular value decomposition image watermarking scheme using human visual system characteristics. IET Image Process. 10(1), 34–52 (2016)
Rahman, S.M.M., Ahmad, M.O., Swamy, M.N.S.: A new statistical detector for DWT-based additive image watermarking using the Gauss-Hermite expansion. IEEE Trans. Image Process. 18(8), 1782–1796 (2009)
Cheng, Q., Huang, T.S.: An additive approach to transform-domain information hiding and optimum detection structure. IEEE Trans. Multimedia 3(3), 273–284 (2001)
Briassouli, A., Tsakalides, P., Stouraitis, A.: Hidden messages in heavy-tails: DCT-domain watermark detection using alpha-stable models. IEEE Trans. Multimedia 7(4), 700–715 (2005)
Akhaee, M.A., Sahraeian, S.M.E.: Robust scaling-based image watermarking using maximum-likelihood decoder with optimum strength factor. IEEE Trans. Multimedia 11(5), 822–833 (2009)
Akhaee, M.A., Sahraeian, S.M.E., Marvasti, F.: Contourlet-based image watermarking using optimum detector in a noisy environment. IEEE Trans. Image Process. 19(4), 967–980 (2010)
Hamghalam, M., Mirzakuchaki, S., Akhaee, M.A.: Geometric modelling of the wavelet coefficients for image watermarking using optimum detector. IET Image Process. 8(3), 162–172 (2014)
Coatrieux, G., Pan, W., Cuppens-Boulahia, N.: Reversible watermarking based on invariant image classification and dynamic histogram shifting. IEEE Trans. Inf. Forensic Secur. 8(1), 111–120 (2013)
Zong, T.R., Xiang, Y., Natgunanathan, I.: Robust histogram shape-based method for image watermarking. IEEE Trans. Circuits Syst. Video Technol. 25(5), 717–729 (2015)
Barni, M., Bartolini, F., De Rosa, A.: Optimum decoding and detection of multiplicative watermarks. IEEE Trans. Signal Process. 51(4), 1118–1123 (2003)
Briassouli, A., Strintzis, M.G.: Locally optimum nonlinearities for DCT watermark detection. IEEE Trans. Image Process. 13(12), 1604–1617 (2004)
Wang, J.W., Liu, G.J.: Locally optimum detection for Barni’s multiplicative watermarking in DWT domain. Signal Process. 88(1), 117–130 (2008)
Kim, H.S., Lee, H.K.: Invariant image watermark using Zernike moments. IEEE Trans. Circuits Syst. Video Technol. 13(8), 766–775 (2003)
Wang, X.Y., Shi, Q.L., Wang, S.M.: A blind robust digital watermarking using invariant exponent moments. AEU-Int. J. Electron. Commun. 70(4), 416–426 (2016)
Li, L.D., Li, S.S., Abraham, A., Pan, J.S.: Geometrically invariant image watermarking using Polar Harmonic Transforms. Inf. Sci. 199(16), 1–19 (2012)
Qi, M., Li, B.Z., Sun, H.F.: Image watermarking using polar harmonic transform with parameters in SL (2, R). Signal Process. Image Commun. 31, 161–173 (2015)
Singh, C., Upneja, R.: Accuracy and numerical stability of high-order polar harmonic transforms. IET Image process. 6(6), 617–626 (2012)
Aziz, I., Haq, F.: A comparative study of numerical integration based on Haar wavelets and hybrid functions. Comput. Math. with Appl. 59(6), 2026–2036 (2010)
Bian, Y., Liang, S.: Image watermark detection in the wavelet domain using Bessel K densities. IET Image Process. 7(4), 281–289 (2013)
Acknowledgement
This work was supported in part by the National Science Foundation of China (NSFC) under Grant No. 61602226; in part by the PhD Startup Foundation of Liaoning Technical University of China under Grant No. 18-1021; in part by Science and Technology Development Plan Project of Taian City under Grant No. 2019GX027.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2021 Springer Nature Switzerland AG
About this paper
Cite this paper
Sang, Y., Bei, Y., Yang, Z., Zhao, C. (2021). Accurate Polar Harmonic Transform-Based Watermarking Using Blind Statistical Detector. In: Yang, M., Chen, C., Liu, Y. (eds) Network and System Security. NSS 2021. Lecture Notes in Computer Science(), vol 13041. Springer, Cham. https://doi.org/10.1007/978-3-030-92708-0_17
Download citation
DOI: https://doi.org/10.1007/978-3-030-92708-0_17
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-92707-3
Online ISBN: 978-3-030-92708-0
eBook Packages: Computer ScienceComputer Science (R0)