Skip to main content
SpringerLink
Log in

Semi-fragile self-recovery watermarking scheme based on data representation through combination

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

Abstract

The widely available multimedia editing tools and their large reconstruction capabilities make digital multimedia content more sensitive to malicious tampering and manipulations. Therefore, ensuring digital image integrity has become a crucial issue. Watermarking became a popular technique for image authentication. The goal of this paper is to propose a new semi-fragile watermarking scheme for image authentication, localization, and recovery, by using two different watermarks jointly. The embedded information watermark for content recovery is computed from discrete wavelet transform (DWT) approximation coefficients of second level decomposition of the original image and compressed by using Data Representation through Combination (DRC) in order to reduce watermark payload. On another hand, authentication watermark used for both authentication and localization of image tampering is computed by using the block-based watermarking algorithm. Three pseudo-random maps are generated in order to improve the security of the proposed scheme against local attack. Both watermarks are embedded into approximation sub-band of the first wavelet decomposition. Experimental results show that our proposed approach has not only an extremely high accuracy of tampering localization but also a relatively very high recovery rate. Besides, the scheme is able to detect perfectly the difference between malicious attacks and non-malicious attacks such as JPEG compression.

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

Access this article

Log in via an institution

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
Fig. 9
Fig. 10
Fig. 11
Fig. 12

Similar content being viewed by others

References

  1. Boneh D, Shoup V (2015) A graduate course in applied cryptography, version 0.2

  2. Chamlawi R, Khan A, Usman I (2010) Authentication and recovery of images using multiple watermarks. Comput Electr Eng 36(3):578–584

    Article  MATH  Google Scholar 

  3. Cheddad A, Condell J, Curran K, Kevitt PM (2010) Digital image steganography: Survey and analysis of current methods. Signal Process 90(3):727–752

    Article  MATH  Google Scholar 

  4. Cox IJIJ (2008) Digital watermarking and steganography. Morgan Kaufmann, San Mateo

    Google Scholar 

  5. Di Martino F, Sessa S (2012) Fragile watermarking tamper detection with images compressed by fuzzy transform. Inform Sci 195:62–90

    Article  Google Scholar 

  6. Haouzia A, Noumeir R (2008) Methods for image authentication: a survey. Multimed Tools Appl 39(1):1–46

    Article  Google Scholar 

  7. He HJ, Zhang JS, Tai HM (2009) Self-recovery fragile watermarking using block-neighborhood tampering characterization. Lecture notes in computer science (including subseries lecture notes in artificial intelligence and lecture notes in bioinformatics) 5806 LNCS:132–145

    Google Scholar 

  8. He H, Chen F, Tai H, Member S, Kalker T, Zhang J (2012) Performance analysis of a block-neighborhood- based self-recovery fragile watermarking scheme. IEEE Trans Inf Forensics Secur 7(1):185–196

    Article  Google Scholar 

  9. Li C, Wang Y, Ma B, Zhang Z (2011) A novel self-recovery fragile watermarking scheme based on dual-redundant-ring structure q. Comput Electr Eng 37:927–940. [Online]. Available: http://or.nsfc.gov.cn/bitstream/00001903-5/88341/1/1000002175455.pdf

    Article  Google Scholar 

  10. Li C, Wang Y, Ma B, Zhang Z (2012) Tamper detection and self-recovery of biometric images using salient region-based authentication watermarking scheme. Computer Standards and Interfaces 34(4):367–379

    Article  Google Scholar 

  11. Li C, Zhang A, Liu Z, Liao L, Huang D (2015) Semi-fragile self-recoverable watermarking algorithm based on wavelet group quantization and double authentication. Multimed Tools Appl 74(23):10581–10604

    Article  Google Scholar 

  12. Lin C-Y, Chang S-F (2000) Semi-fragile watermarking for authenticating JPEG visual content. In: Proceedings of the SPIE security and watermarking of multimedia contents II, San Jose, pp 140–151

  13. Ling C, Ur-rehman O (2015) Robust image authentication in the presence of noise. Springer, Cham, pp 43–53

    Google Scholar 

  14. Liu C-L (2010) A tutorial of the wavelet transform Chapter 1 Overview 1.1 Introduction

  15. Ouled Zaid A, Makhloufi A, Bouallegue A, Olivier C (2009) Improved QIM-based watermarking integrated to JPEG2000 coding scheme. SIViP 3(3):197–207

    Article  MATH  Google Scholar 

  16. Phadikar A, Maity SP, Mandal M (2012) Novel wavelet-based QIM data hiding technique for tamper detection and correction of digital images. J Vis Commun Image Represent 23(3):454–466

    Article  Google Scholar 

  17. Poornima R, Iswarya R (2013) And overview of digital image steganography. International Journal of Computer Science & Engineering Survey 4(1):23–31

    Article  Google Scholar 

  18. Preda RO (2013) Semi-fragile watermarking for image authentication with sensitive tamper localization in the wavelet domain. Measurement 46(1):367–373

    Article  MathSciNet  Google Scholar 

  19. Qi X, Xin X (2011) A quantization-based semi-fragile watermarking scheme for image content authentication. J Vis Commun Image Represent 22:187–200

    Article  Google Scholar 

  20. Qi X, Xin X (2015) A singular-value-based semi-fragile watermarking scheme for image content authentication with tamper localization. J Vis Commun Image Represent 30:312–327

    Article  Google Scholar 

  21. Said J, Souissi R, Hamam H (2013) A new representation of image through numbering pixel combinations. Journal of Information Security Research 4:1

    Article  Google Scholar 

  22. Salomon D (2007) Data compression: the complete reference. Springer, Berlin

    MATH  Google Scholar 

  23. Salomon D (2008) A concise introduction to data compression, ser. Undergraduate topics in computer science. Springer, London

    Book  Google Scholar 

  24. Sayood K (2006) Introduction to data compression, Third edition (Morgan Kaufmann Series in multimedia information and systems)

  25. Tong X, Liu Y, Zhang M, Chen Y (2013) A novel chaos-based fragile watermarking for image tampering detection and self-recovery. Signal Process Image Commun 28(3):301–308

    Article  Google Scholar 

  26. Tsai T, Wu C, Fang C (2014) Design and Implementation of a joint data compression and digital watermarking system in an MPEG-2 video encoder. J Sign Process Syst 74:203

    Article  Google Scholar 

  27. Ullah R, Khan A, Malik AS (2013) Dual-purpose semi-fragile watermark: Authentication and recovery of digital images. Comput Electr Eng 39 (7):2019–2030. [Online]. Available: https://www.sciencedirect.com/science/article/pii/S0045790613001213

    Article  Google Scholar 

  28. Wang H, Ho AT, Zhao X (2012) A novel fast self-restoration semi-fragile watermarking algorithm for image content authentication resistant to JPEG compression. Lecture notes in computer science (including subseries lecture notes in artificial intelligence and lecture notes in bioinformatics) 7128 LNCS:72–85

    Google Scholar 

  29. Wang Z, Bovik AC, Sheikh HR, Member S, Simoncelli EP, Member S (2004) Image quality assessment : from error visibility to structural similarity. IEEE Trans Image Process 13(4):1–14

    Article  Google Scholar 

  30. Wu C-M, Shih Y-S (2013) A simple image tamper detection and recovery based on fragile watermark with one parity section and two restoration sections. Optics and Photonics Journal 03(02):103–107

    Article  Google Scholar 

  31. Xiao D, Shih FY (2012) An improved hierarchical fragile watermarking scheme using chaotic sequence sorting and subblock post-processing. Opt Commun 285 (10–11):2596–2606. [Online]. Available: https://www.sciencedirect.com/science/article/abs/pii/S0030401812001368

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. École Nationale d’Ingénieurs de Gabés (ENIG), Université de Gabés, Omar Ibn El Khattab Zrig, Gabés, 6072, Tunisia

    Hanen Rhayma

  2. ATMS Advanced Technologies for Medecine and Signals, Enis, Université de Sfax, Sfax, Tunisia

    Hanen Rhayma, Achraf Makhloufi & Ahmed Ben Hamida

  3. Faculty of Engineering, Université de Moncton, Moncton, NB, E1A 3E9, Canada

    Habib Hamam

Authors
  1. Hanen Rhayma
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Achraf Makhloufi
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Habib Hamam
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Ahmed Ben Hamida
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Hanen Rhayma.

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

Rhayma, H., Makhloufi, A., Hamam, H. et al. Semi-fragile self-recovery watermarking scheme based on data representation through combination. Multimed Tools Appl 78, 14067–14089 (2019). https://doi.org/10.1007/s11042-019-7244-x

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11042-019-7244-x

Keywords

Search

Navigation