Skip to main content
Log in

An SVD-based screen-shooting resilient watermarking scheme

  • Published:
Multimedia Tools and Applications Aims and scope Submit manuscript

Abstract

This paper proposes a new watermarking scheme that is screen-shooting resilient. We try to design a watermarking scheme that can resist the distortion generated during the screen-shooting process while has a good invisibility. While embedding, we utilize the stability of the singular value matrix in terms of sign invariance to improve the robustness of our watermarking scheme. We use scale-invariant feature transform (SIFT) algorithm to help with locating different embedding regions to embed repeatedly to further improve robustness. While extracting, we located more regions compared with embedding process to enhance the error-tolerant rate. Compared with the previous method, our watermarking scheme has a larger embedding capacity while performing better in terms of robustness and invisibility.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8

Similar content being viewed by others

References

  1. Arora M, Kumar M (2021) AutoFER: PCA and PSO based automatic facial emotion recognition. Multimed Tools Appl 80(2):3039–3049

    Article  Google Scholar 

  2. Bansal M, Kumar M, Kumar M (2020) 2D Object recognition techniques: state-of-the-art work. Archives of Computational Methods in Engineering, 1-15

  3. Bansal M, Kumar M, Kumar M et al (2021) An efficient technique for object recognition using Shi-Tomasi corner detection algorithm. Soft Comput 25 (6):4423–4432

    Article  Google Scholar 

  4. Barni M, Bartolini F, Cappellini V, et al. (1998) A DCT-domain system for robust image watermarking. Signal processing, 1998 66(3):357–372

    MATH  Google Scholar 

  5. Chandra DVS (2002) Digital image watermarking using singular value decomposition

  6. Chang CC, Tsai P, Lin CC (2005) SVD-Based digital image watermarking scheme. Pattern Recogn Lett 26(10):1577–1586

    Article  Google Scholar 

  7. Chhabra P, Garg NK, Kumar M (2020) Content-based image retrieval system using ORB and SIFT features. Neural Comput & Applic 32(7):2725–2733

    Article  Google Scholar 

  8. Chu WC (2003) DCT-Based image watermarking using subsampling. IEEE Transactions on Multimedia 5(1):34–38. https://doi.org/10.1109/TMM.2003.808816

    Article  Google Scholar 

  9. Chung KL, Yang WN, Huang YH, Wu ST, Hsu YC (2007) On SVD-based watermarking algorithm. Appl Math Comput, 54–57

  10. Ganic E, Eskicioglu AM (2004) Robust DWT-SVD domain image watermarking: embedding data in all frequencies. In: Proceedings of the 2004 workshop on multimedia and security, vol 2004, pp 166–174

  11. Gupta S, Kumar M (2020) Forensic document examination system using boosting and bagging methodologies. Soft Comput 24(7):5409–5426

    Article  Google Scholar 

  12. Gupta S, Mohan. N, Kumar M (2020) A Study on Source Device Attribution Using Still Images. Arch Computat Methods Eng

  13. Hai T, Li CM, Zain JM, Abdalla AN (2014) Robust Image watermarking theories and techniques: A review. J Appl Res Technol 12(1):122–138

    Article  Google Scholar 

  14. Han F, Zhang WM, Zhou H et al (2018) Screen-shooting resilient watermarking. IEEE Transactions on Information Forensics and Security 14(6):1403–1418

    Google Scholar 

  15. Hsu CT, Wu JL (1999) Hidden Digital watermarks in images. IEEE Trans Image Process 8(1):58–68. https://doi.org/10.1109/83.736686

    Article  Google Scholar 

  16. Kang X, Huang J, Zeng W (2010) Efficient General print-scanning resilient data hiding based on uniform log-polar mapping. IEEE Transactions on Information Forensics and Security 5(1):1–12

    Article  Google Scholar 

  17. Kaur RP, Jindal MK, Kumar M (2020) Text and graphics segmentation of newspapers printed in Gurmukhi script: a hybrid approach. Vis Comput, 1–23

  18. Kumar M, Chhabra P, Garg NK (2018) An efficient content based image retrieval system using BayesNet and k-NN. Multimed Tools Appl 77 (16):21557–21570

    Article  Google Scholar 

  19. Kumar M, Kumar M (2021) XGBOost: 2D-Object Recognition Using Shape Descriptors and Extreme Gradient Boosting Classifier. Computational Methods and Data Engineering. Springer, Singapore, pp 207–222

    Google Scholar 

  20. Kumar A, Kumar M, Kaur A (2021) Face detection in still images under occlusion and non-uniform illumination. Multimed Tools Appl 80(10):14565–14590

    Article  Google Scholar 

  21. Liu RZ, Tan TN (2002) An SVD-based watermarking scheme for protecting rightful ownership. IEEE Transactions on Multimedia 4(1):121–128

    Article  Google Scholar 

  22. Liu X, Wang Y, Du J, et al. (2019) Robust hybrid image watermarking scheme based on KAZE features and IWT-SVD. Multimed Tools Appl 78 (5):6355–6384

    Article  Google Scholar 

  23. Lowe DG (1999) Object recognition from local scale-invariant features. Proceedings of the seventh. IEEE International Conference on Computer Vision. Ieee 1999(2):1150–1157

    MathSciNet  Google Scholar 

  24. Lowe DG (2004) (2004) Distinctive Image features from scale-invariant keypoints. Int J Comput Vis 60(2):91–110

    Article  Google Scholar 

  25. Mezirow J (1978) Perspective transformation. Adult Education 28 (2):100–110

    Article  Google Scholar 

  26. Poonam ASM (2018) A DWT-SVD based Robust Digital Watermarking for Digital Images. Procedia Computer Science, 1441–1448, vol 132

  27. Premaratne P, Ko CC (1999) A novel watermark embedding and detection scheme for images in DFT domain. In: 7th international conference on image processing and its applications, vol 1999, pp 780–783

  28. Prins JP, Erkin Z, Lagendijk RL (2007) Anonymous fingerprinting with robust QIM watermarking techniques. EURASIP Journal on Information Security, 2007 2007(1):031340

    Article  Google Scholar 

  29. Raval MS, Rege PP (2003) Discrete wavelet transform based multiple watermarking scheme. TENCON 2003. Conference on Convergent Technologies for Asia-Pacific Region IEEE 2003(3):935–938

    Article  Google Scholar 

  30. Tao PN, Eskicioglu AM (2004) A robust multiple watermarking scheme in the discrete wavelet transform domain. Internet Multimedia Management Systems V. International Society for Optics and Photonics 2004(5601):133–144

    Google Scholar 

  31. Tirkel AZ, Rankin GA, Schyndel RMV, Ho WJ, Mee NRA, Osborne CF (1993) Electronic Watermark. Digital Image Computing. Technology and Applications (DICTA’93), 666–673

  32. Urvoy M, Goudia D, Autrusseau F (2014) Perceptual DFT watermarking with improved detection and robustness to geometrical distortions. IEEE Transactions on Information Forensics and Security 9(7):1108–1119

    Article  Google Scholar 

  33. Wengrowski E, Dana K (2019) Light field messaging with deep photographic steganography. In: Proceedings of the IEEE conference on computer vision and pattern recognition, vol 2019, pp 1515–1524

  34. Wolfgang RB, Delp IIIEJ (1999) Fragile watermarking using the VW2d watermark. Security and Watermarking of Multimedia Contents. International Society for Optics and Photonics 1999(3657):204–213

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Biao Deng.

Additional information

Publisher’s note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Deng, B., Li, S. & Qian, Z. An SVD-based screen-shooting resilient watermarking scheme. Multimed Tools Appl 81, 32841–32855 (2022). https://doi.org/10.1007/s11042-022-12738-x

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11042-022-12738-x

Keywords

Navigation