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SCIENTIA SINICA Informationis, Volume 48, Issue 1: 79-99(2018) https://doi.org/10.1360/N112017-00109

Stereo image zero-watermarking algorithm based on ternary polar harmonic Fourier moments and chaotic mapping

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  • ReceivedMay 16, 2017
  • AcceptedAug 1, 2017
  • PublishedNov 16, 2017

Abstract

In recent years, stereo images have attracted extensive attention because of their strong immersion, and the corresponding copyright protection of stereo images is becoming increasingly urgent. At present, most of the watermarking algorithms for image copyright protection are aimed at planar images, and there are few watermarking algorithms for stereo images. Moreover, most of the existing stereo image watermarking algorithms are not very good at reflecting and retaining the specific relationship between the left and right views of the stereo images, which will inevitably affect the robustness of the algorithm. In this paper, ternary polar harmonic Fourier moments (TPHFM) for stereo images is proposed and based on this and chaotic mapping, a robust stereo image zero-watermarking algorithm is presented. First, mixed linear-nonlinear coupled map lattice is used to make the original binary logo image chaotic. Next, the TPHFM of the original stereo image is computed and accurate moments for the zero-watermarking algorithm are selected. Then, the binary feature image is constructed using the accurate moments, and scrambled using Sine mapping and Cosine mapping. Finally, a zero-watermark image is generated using the exclusive-or on the scrambled binary feature image and the chaotic binary logo image. Experimental results show that the proposed zero-watermarking algorithm is excellently robust against common image processing attacks and geometric attacks, and is superior to ternary radial harmonic Fourier moments (TRHFM)-based algorithm and other zero-watermarking algorithms.


Funded by

国家自然科学基金(61370145)

“十三五国家密码发展基金(MMJJ20170203)

国家自然科学基金(61672124)

国家自然科学基金(61173183)


References

[1] Wang X Y, Meng L, Yang H Y. A color image digital watermarking algorithm based on multiscale features. Sci China Ser F-Inf Sci, 2009, 39: 966--976. Google Scholar

[2] Lu J, Zou Y R, Yang C Y, et al. A robust fractal color image watermarking algorithm. Math Probl Eng, 2014, 2014: 26--44. Google Scholar

[3] Wen Q, Sun T F, Wang S X. Based zero-watermark digital watermarking technology. In: Proceedings of the 3rd National Conference in Information Hiding. Xian: Xidian University Press, 2001. 102--109. Google Scholar

[4] Wen Q, Sun T F, Wang S X. Concept and application of zero-watermark. Acta Electron Sin, 2003, 31: 214--216. Google Scholar

[5] Chen T H, Horng G B, Lee W B. A publicly verifiable copyright-proving scheme resistant to malicious attacks. IEEE Trans Ind Electron, 2005, 52: 327--334. Google Scholar

[6] Chang C C, Lin P Y. Adaptive watermark mechanism for rightful ownership protection. J Syst Softw, 2008, 81: 1118--1129. Google Scholar

[7] Tsai H H, Tseng H C, Lai Y S. Robust lossless image watermarking based on $\alpha$-trimmed mean algorithm and support vector machine. J Syst Softw, 2010, 83: 1015--1028. Google Scholar

[8] Tsai H H, Lai Y S, Lo S C. A zero-watermark scheme with geometrical invariants using SVM and PSO against geometrical attacks for image protection. J Syst Softw, 2013, 86: 335--348. Google Scholar

[9] Gao G Y, Jiang G P. Bessel-Fourier moment-based robust image zero-watermarking. Multimed Tools Appl, 2013, 74: 841--858. Google Scholar

[10] Sun L, Xu J C, Zhang X X, et al. A novel generalized Arnold transform-based zero-watermarking scheme. Appl Math Inf Sci, 2015, 4: 2023--2035. Google Scholar

[11] Zhou W J, Yu M, Yu S M, et al. A zero-watermarking algorithm of stereoscopic image based on hyperchaotic system. Acta Phys Sin, 2012, 61: 117--126. Google Scholar

[12] Wang C P, Wang X Y, Xia Z Q, et al. Geometrically resilient color image zero-watermarking algorithm based on quaternion exponent moments. J Vis Commun Image Represent, 2016, 41: 247--259. Google Scholar

[13] Wang C, Wang X, Chen X. Robust zero-watermarking algorithm based on polar complex exponential transform and logistic mapping. Multimed Tools Appl, 2017, 76: 26355-26376 CrossRef Google Scholar

[14] Hamilton W R. Elements of Quaternions. London: Longmans, Green, and Company, 1899. Google Scholar

[15] Wang X Y, Wang C P, Yang H Y, et al. A robust blind color image watermarking in quaternion Fourier transform domain. J Syst Softw, 2013, 86: 255--277. Google Scholar

[16] Ren H P, Ping Z L, Bo W R G, et al. Multidistortion-invariant image recognition with radial harmonic Fourier moments. J Opt Soc Am Opt Image Sci Vis, 2003, 20: 631--637. Google Scholar

[17] Wang C P, Wang X Y, Xia Z Q. Geometrically invariant image watermarking based on fast radial harmonic Fourier moments. Signal Process Image Commun, 2016, 45: 10--23. Google Scholar

[18] Singh C, Upneja R. Error analysis in the computation of orthogonal rotation invariant moments. J Math Imaging Vis, 2014, 49: 251--271. Google Scholar

[19] Xin Y Q, Liao S, Pawlak M. Circularly orthogonal moments for geometrically robust image watermarking. Pattern Recogn, 2007, 40: 3740--3752. Google Scholar

[20] Li L D, Li S S, Abraham A, et al. Geometrically invariant image watermarking using polar harmonic transforms. Inf Sci, 2012, 199: 1--19. Google Scholar

[21] Zhang Y Q, Wang X Y. Spatiotemporal chaos in mixed linear-nonlinear coupled logistic map lattice. Phys A, 2014, 402: 104--118. Google Scholar

[22] Pareek N K, Patidar V, Sud K K. Image encryption using chaotic logistic map. Image Vis Comput, 2006, 24: 926--934. Google Scholar

[23] Tang Z J, Zhang X Q, Huang L Y, et al. Robust image hashing using ring-based entropies. Signal Process, 2013, 93: 2061--2069. Google Scholar

[24] Tang Z J, Zhang X Q, Zhang S C. Robust perceptual image hashing based on ring partition and NMF. IEEE Trans Knowl Data Eng, 2014, 26: 711--724. Google Scholar

[25] Tang Z J, Zhang X Q, Li X X, et al. Robust image hashing with ring partition and invariant vector distance. IEEE Trans Inf Forensic Secur, 2016, 11: 200--214. Google Scholar

[26] Scharstein D, Pal C. Learning conditional random fields for stereo. In: Proceedings of 2007 IEEE Conference on Computer Vision and Pattern Recognition, Minneapolis, 2007. Google Scholar

[27] Hirschmuller H, Scharstein D. Evaluation of cost functions for stereo matching. In: Proceedings of 2007 IEEE Conference on Computer Vision and Pattern Recognition, Minneapolis, 2007. Google Scholar

[28] Lu J, Ye Z X, Zou Y R. Huber fractal image coding based on a fitting plane. IEEE Trans Image Process, 2013, 22: 134--145. Google Scholar

[29] Lu J, Shen L X, Xu C, et al. Multiplicative noise removal in imaging: an exp-model and its fixed-point proximity algorithm. Appl Comput Harmon Anal, 2015, 41: 518--539. Google Scholar

[30] Gong D F, Liu F L, Luo X Y. An image edge based robust watermarking algorithm. Sci Sin Inform, 2013, 43: 1410--1430. Google Scholar

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