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3D Video watermarking for MVD based view-synthesis and RST attack

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Abstract

Security in terms of copyright measurement for digital media distribution is the most challenging task. To maintain the digital right in 3D media, a watermarking scheme is proposed for Multi-view Video plus Depth (MVD) representation to sustain against the view synthesis and RST attack. The Singular Value Decomposition (SVD) is carried out on the left and the right video sequences to find view-invariant coefficients for watermark insertion. Motion compensated Discrete Cosine Transform (DCT) based Temporal Filtering (MCDCT-TF) is used in the temporal direction to make the scheme robust against video compression attack. The 2D Discrete Wavelet Transform (2D-DWT ) is processed on the temporally filtered low-pass frames as a pre-processing to get to make the SVD coefficients more connected or say correlated in between the 3D view such that robustness can be achieved against RST and view synthesis with minimum visual degradation. A set of experiments is carried out with different 3D video sequences to justify the robustness of the proposed scheme over the RST attack.

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Notes

  1. “http://www.tanimoto.nuee.nagoya-u.ac.jp/~fukushima/mpegftv/” “http://www.merl.com/pub/tian/NICT-3D/”

  2. “http://mmspg.epfl.ch/vqmt”

References

  1. Anderson R, Kingsbury N, Fauqueur J (2005) Determining multiscale image feature angles from complex wavelet phases. In: Kamel M, Campilho A (eds) Image Analysis and Recognition. Springer, Berlin, Heidelberg, pp 490–498

    Chapter  Google Scholar 

  2. Atta R, Ghanbari M (2006) Spatio-temporal scalability-based motioncompensated 3-d subband/dct video coding. Circuits and Systems for Video Technology, IEEE Transactions on 16(1):43–55. https://doi.org/10.1109/TCSVT.2005.858743

    Article  Google Scholar 

  3. Bentley PM, McDonnell JTE (1994) Wavelet transforms: an introduction. Electronics Communication Engineering Journal 6(4):175–186. https://doi.org/10.1049/ecej:19940401

    Article  Google Scholar 

  4. Bosse S, Schwarz H, Hinz T, Wiegand T (2012) Encoder control for renderable regions in high efficiency multiview video plus depth coding. In: 2012 Picture Coding Symposium, pp. 129–132. https://doi.org/10.1109/PCS.2012.6213303

  5. Campisi P (2008) Object-oriented stereo-image digital watermarking. Journal of Electronic Imaging 17(4):043024–0430245. https://doi.org/10.1117/1.3009554

    Article  ADS  Google Scholar 

  6. Chen L, Zhao J (2020) A robust blind watermarking algorithm for depthimage-based rendering 3d images. Signal Processing: Image Communication 87:115935

    Google Scholar 

  7. Chen Y, Tech G, Wegner K, Yea S, Electronics L (2015) Test Model 11 of 3D–HEVC and MV–HEVC, Jct3v–j1003 edn. Joint Collaborative Team on 3D Video Coding Extension Development of ITU–T SG 16 WP 3 and ISO/IEC JTC 1/SC 29/WG 11. Joint Collaborative Team on 3D Video Coding Extension Development of ITU–T SG 16 WP 3 and ISO/IEC JTC 1/SC 29/WG 11

  8. Choi S-J, Woods JW (1999) Motion-compensated 3-d subband coding of video. IEEE Trans Image Process 8(2):155–167. https://doi.org/10.1109/83.743851

    Article  ADS  CAS  PubMed  Google Scholar 

  9. Do MN, Vetterli M (2003) The finite ridgelet transform for image representation. IEEE Trans Image Process 12(1):16–28

    Article  ADS  MathSciNet  PubMed  Google Scholar 

  10. Egiazarian K, Astola J, Ponomarenko N, Lukin V, Battisti F, Carli M (2006) New full–reference quality metrics based on hvs. In: CD–ROM Proceedings of the Second International Workshop on Video Processing and Quality Metrics, Scottsdale, USA, vol. 4

  11. Etoom W, Al-Haj A (2022) A robust and imperceptible watermarking method for 3d dibr images. Multimedia Tools and Applications 81(20):28165–28182

    Article  Google Scholar 

  12. Fan Y-C, Chi T-C (2008) The novel non-hole-filling approach of depth image based rendering. In: 3DTV Conference: The True Vision–Capture, Transmission and Display of 3D Video, 2008, pp. 325–328. https://doi.org/10.1109/3DTV.2008.4547874

  13. Fehn C, Pastoor RS (2006) Interactive 3-dtv-concepts and key technologies. Proc IEEE 94(3):524–538. https://doi.org/10.1109/JPROC.2006.870688

    Article  Google Scholar 

  14. Flierl M, Girod B (2004) Video coding with motion-compensated lifted wavelet transforms. Signal Processing: Image Communication 19(7):561–575. https://doi.org/10.1016/j.image.2004.05.002. Special Issue on Subband/Wavelet Interframe Video Coding

  15. Franco-Contreras J, Baudry S, Doerr G (2011) Virtual view invariant domain for 3d video blind watermarking. In: Image Processing (ICIP), 2011 18th IEEE International Conference On, pp. 2761–2764. https://doi.org/10.1109/ICIP.2011.6116242

  16. Gaj S, Rana S, Lekharu A, Sur A, Bora PK (2015) Rst invariant multi view 3d image watermarking using dwt and svd. In: 2015 Fifth National Conference on Computer Vision, Pattern Recognition, Image Processing and Graphics (NCVPRIPG), pp. 1–4. https://doi.org/10.1109/NCVPRIPG.2015.7490066

  17. Garcia E, Dugelay J (2003) Texture-based watermarking of 3d video objects. Circuits and Systems for Video Technology, IEEE Transactions on 13(8):853–866. https://doi.org/10.1109/TCSVT.2003.815963

    Article  Google Scholar 

  18. Ghanbari M (1990) The cross-search algorithm for motion estimation [image coding]. IEEE Trans Commun 38(7):950–953. https://doi.org/10.1109/26.57512

    Article  Google Scholar 

  19. Halici E, Alatan AA (2009) Watermarking for depth-image-based rendering. In: Image Processing (ICIP), 2009 16th IEEE International Conference On, pp. 4217–4220. https://doi.org/10.1109/ICIP.2009.5413525

  20. Hoffman DM, Girshick AR, Akeley K, Banks MS (2008) Vergence-accommodation conflicts hinder visual performance and cause visual fatigue. J Vis 8(3):33

    Article  Google Scholar 

  21. Holmes M, Gray A, Isbell C (2007) Fast svd for large-scale matrices. Workshop on Efficient Machine Learning at NIPS 58:249–252

    Google Scholar 

  22. Hui C, Liu S, Cui W, Zeng J, Jiang F, Zhao D (2021) Adaptive flexible 3d histogram watermarking. In: 2021 IEEE International Conference on Multimedia and Expo (ICME), pp. 1–6. IEEE

  23. Jain V, Mangal A (2021) A novel 3d object watermarking technique using hash key cryptography. In: 2021 International Conference on Artificial Intelligence and Smart Systems (ICAIS), pp. 1122–1126. IEEE

  24. Jaipuria SJ (2014) Watermarking for depth map based 3d images using wavelet transform. In: Communications and Signal Processing (ICCSP), 2014 International Conference On, pp. 181–185. https://doi.org/10.1109/ICCSP.2014.6949824

  25. Jridi, M., Ouerhani, Y., Alfalou, A.: Low Complexity DCT Engine for Image and Video Compression. https://doi.org/10.1117/12.2006174

  26. Kauff P, Atzpadin N, Fehn C, Müller M, Schreer O, Smolic A, Tanger R (2007) Depth map creation and image-based rendering for advanced 3dtv services providing interoperability and scalability. Signal Processing: Image Communication 22(2):217–234. https://doi.org/10.1016/j.image.2006.11.013. Special issue on three-dimensional video and television

  27. Kim H-D, Lee J-W, Oh T-W, Lee H-K (2012) Robust dt-cwt watermarking for dibr 3d images. Broadcasting, IEEE Transactions on 58(4):533–543. https://doi.org/10.1109/TBC.2012.2206851

    Article  Google Scholar 

  28. Koley S (2022) Bat optimized 3d anaglyph image watermarking based on maximum noise fraction in the digital shearlet domain. Multimedia Tools and Applications 81(14):19491–19523

    Article  Google Scholar 

  29. Lee M-J, Lee J-w, Lee H-K (2011) Perceptual watermarking for 3d stereoscopic video using depth information. In: Intelligent Information Hiding and Multimedia Signal Processing (IIH-MSP), 2011 Seventh International Conference On, pp. 81–84. https://doi.org/10.1109/IIHMSP.2011.83

  30. Lin Y-H, Wu J-L (2011) A digital blind watermarking for depth-image-based rendering 3d images. Broadcasting, IEEE Transactions on 57(2):602–611. https://doi.org/10.1109/TBC.2011.2131470

    Article  ADS  Google Scholar 

  31. Liu X, Wang Y, Sun Z, Wang L, Zhao R, Zhu Y, Zou B, Zhao Y, Fang H (2021) Robust and discriminative zero-watermark scheme based on invariant features and similarity-based retrieval to protect large-scale dibr 3d videos. Inf Sci 542:263–285

    Article  MathSciNet  Google Scholar 

  32. Luo Y, Peng D (2021) A robust digital watermarking method for depth-imagebased rendering 3d video. Multimedia Tools and Applications 80:14915–14939

    Article  Google Scholar 

  33. Nam KM, Kim J-S, Park R-H, Shim YS (1995) A fast hierarchical motion vector estimation algorithm using mean pyramid. IEEE Transactions on Circuits and Systems for Video Technology 5(4):344–351. https://doi.org/10.1109/76.465087

    Article  Google Scholar 

  34. Po L-M, Ma W-C (1996) A novel four-step search algorithm for fast block motion estimation. IEEE Transactions on Circuits and Systems for Video Technology 6(3):313–317. https://doi.org/10.1109/76.499840

    Article  ADS  Google Scholar 

  35. Rana, S., Sur A (2015) 3D video watermarking using DT–DWT to resist synthesis view attack. In: 23rd European Signal Processing Conference (EUSIPCO) (EUSIPCO 2015), Nice, France

  36. Rana S, Sahu N, Sur A (2014) Robust watermarking for resolution and quality scalable video sequence. Multimedia Tools and Applications 1–30. https://doi.org/10.1007/s11042-014-2023-1

  37. Rana S, Gaj S, Sur A, Bora PK (2022) Classification of real 3d and fake 3d video. IETE J Res 68(2):947–956. https://doi.org/10.1080/03772063.2019.1628667

    Article  Google Scholar 

  38. Rana S, Sur A (2014) Blind 3d video watermarking based on 3d-hevc encoder using depth. In: Proceedings of the Ninth Indian Conference on Computer Vision, Graphics and Image Processing. ICVGIP’ 14. ACM, New York, NY, USA. https://doi.org/10.1145/2683483.2683535

  39. Schwarz H, Wiegand T (2012) Inter-view prediction of motion data in multiview video coding. In: 2012 Picture Coding Symposium, pp. 101–104. https://doi.org/10.1109/PCS.2012.6213296

  40. Sheikh HR, Bovik AC (2006) Image information and visual quality. IEEE Trans Image Process 15(2):430–444. https://doi.org/10.1109/TIP.2005.859378

    Article  ADS  PubMed  Google Scholar 

  41. Sheng-li F, Mei Y, Gang-yi J, Feng S, Zong-ju P (2012) A digital watermarking algorithm based on region of interest for 3d image, 549–552. https://doi.org/10.1109/CIS.2012.129

  42. Verdicchio F, Andreopoulos Y, Clerckx T, Barbarien J, Munteanu A, Cornelis J, Schelkens P (2004) Scalable video coding based on motioncompensated temporal filtering: complexity and functionality analysis. In: Image Processing, 2004. ICIP ’04. 2004 International Conference On, vol. 5, pp. 2845–28485. https://doi.org/10.1109/ICIP.2004.1421705

  43. Vinod P, Bora PK (2006) Motion-compensated inter-frame collusion attack on video watermarking and a countermeasure. Information Security, IEE Proceedings 153(2):61–73

    Article  Google Scholar 

  44. Wang Z, Bovik AC, Sheikh HR, Simoncelli EP (2004) Image quality assessment: from error visibility to structural similarity. IEEE Trans Image Process 13(4):600–612. https://doi.org/10.1109/TIP.2003.819861

    Article  ADS  PubMed  Google Scholar 

  45. Zahariadis T, Kalivas D (1996) A spiral search algorithm for fast estimation of block motion vectors. In: European Signal Processing Conference, 1996. EUSIPCO 1996. 8th, pp. 1–4

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Acknowledgements

Ms Usha Kumari, PhD Scholar of SRM University AP, has given substantial input to improve the revised version of the manuscript. Her contribution towards the technical writing of this paper is commendable.

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  1. Visual Information Processing LAB,Departmentof CSE, SRM University AP, Neerukonda, Mangalagiri, 522240, Andhra Pradesh, India

    Shuvendu Rana

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Rana, S. 3D Video watermarking for MVD based view-synthesis and RST attack. Multimed Tools Appl 83, 26775–26795 (2024). https://doi.org/10.1007/s11042-023-16481-9

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