Advertisement

Image tamper detection and self-recovery using multiple median watermarking

  • Vishal Rajput
  • Irshad Ahmad AnsariEmail author
Article
  • 58 Downloads

Abstract

Photographs play a very crucial role in our lives, be it in the field of forensic investigation, military intelligence, scientific research, and publications. Nowadays, most of these photographs are in the digital format; which can be easily edited in any photo editing software without requiring any special knowledge of the field. It has become quite hard to identify whether an image is real or fake. This can be very crucial in the cases of forensic investigation or authorization of images. So, we need a solution, which not only identifies the attacks from different schemes like collage attack, crop attack, etc. but also recovers the edited or tampered portion. In proposed work, 4 reduced-size copy of the original image is hidden in the original image’s 4-LSB using four pseudo-random codes. Later on, these copies are used for tamper detection. As image gets tampered, recovery images (which are stored in the 4-LSB’s of the original image) also get tampered. So, before recovering the edited portion using the median image (or one out of the four recovery images) various filters like median filters, sharpening filters, and noise removal filters are used to enhance the quality. The proposed scheme recovers the host better than the many recently proposed schemes.

Keywords

Tamper detection Self-recovery Median watermarking Image watermarking Image security 

Notes

Acknowledgements

This work was supported by Faculty Initiation Grant of PDPM Indian Institute of Information Technology Design and Manufacturing Jabalpur, India.

References

  1. 1.
    Cao F, An B, Wang J, Ye D, Wang H (2017) Hierarchical recovery for tampered images based on watermark self-embedding. Displays 46:52–60CrossRefGoogle Scholar
  2. 2.
    Celik MU, Sharma G, Saber E, Tekalp AM (2002) Hierarchical watermarking for secure image authentication with localization. IEEE Trans Image Process 11(6):585–595CrossRefGoogle Scholar
  3. 3.
    Chang YF, Tai WL (2013) A block-based watermarking scheme for image tamper detection and self-recovery. Opto-Electron Rev 21(2):182–190MathSciNetCrossRefGoogle Scholar
  4. 4.
    Chang CC, Fan YH, Tai WL (2008) Four-scanning attack on hierarchical digital watermarking method for image tamper detection and recovery. Pattern Recogn 41(2):654–661CrossRefzbMATHGoogle Scholar
  5. 5.
    Fridrich J (2002) Security of fragile authentication watermarks with localization. In Security and Watermarking of Multimedia Contents IV (Vol. 4675, pp 691–701). International Society for Optics and PhotonicsGoogle Scholar
  6. 6.
    He HJ, Zhang JS, Chen F (2009) Adjacent-block based statistical detection method for self-embedding watermarking techniques. Signal Process 89(8):1557–1566CrossRefzbMATHGoogle Scholar
  7. 7.
    He H, Chen F, Tai HM, Kalker T, Zhang J (2012) Performance analysis of a blockneighborhood-based self-recovery fragile watermarking scheme. IEEE Trans Inf Forensics Secur 7(1):185–196CrossRefGoogle Scholar
  8. 8.
    Hore A, Ziou D (2010) Image quality metrics: PSNR vs. SSIM. In 2010 20th International Conference on Pattern Recognition (pp 2366–2369). IEEEGoogle Scholar
  9. 9.
    Islam M, Roy A, Laskar RH SVM-based robust image watermarking technique in LWT domain using different sub-bands. Neural Comput Applic 1–25Google Scholar
  10. 10.
    Izquierdo E, Guerra V (2003) An ill-posed operator for secure image authentication. IEEE Trans Circuits Syst Video Technol 13(8):842–852CrossRefGoogle Scholar
  11. 11.
    Korus P, Dziech A (2014) Adaptive self-embedding scheme with controlled reconstruction performance. IEEE Trans Inf Forensics Secur 9(2):169–181CrossRefGoogle Scholar
  12. 12.
    Kundur D, Hatzinakos D (1999) Digital watermarking for telltale tamper proofing and authentication. Proc IEEE 87(7):1167–1180CrossRefGoogle Scholar
  13. 13.
    Lee TY, Lin SD (2008) Dual watermark for image tamper detection and recovery. Pattern Recogn 41(11):3497–3506MathSciNetCrossRefzbMATHGoogle Scholar
  14. 14.
    Li J, Li X, Yang B, Sun X (2015) Segmentation-based image copy-move forgery detection scheme. IEEE Trans Inf Forensics Secur 10(3):507–518CrossRefGoogle Scholar
  15. 15.
    Lin PL, Hsieh CK, Huang PW (2005) A hierarchical digital watermarking method for image tamper detection and recovery. Pattern Recogn 38(12):2519–2529CrossRefGoogle Scholar
  16. 16.
    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 30:312–327CrossRefGoogle Scholar
  17. 17.
    Qian Z, Feng G, Zhang X, Wang S (2011) Image self-embedding with high-quality restoration capability. Digital Signal Process 21(2):278–286CrossRefGoogle Scholar
  18. 18.
    Sarreshtedari S, Akhaee MA (2015) A source-channel coding approach to digital image protection and self-recovery. IEEE Trans Image Process 24(7):2266–2277MathSciNetCrossRefzbMATHGoogle Scholar
  19. 19.
    Shehab A, Elhoseny M, Muhammad K, Sangaiah AK, Yang P, Huang H, Hou G (2018) Secure and robust fragile watermarking scheme for medical images. IEEE Access 6:10269–10278CrossRefGoogle Scholar
  20. 20.
    Singh D, Singh SK (2016) Effective self-embedding watermarking scheme for image tampered detection and localization with recovery capability. J Vis Commun Image Represent 38:775–789CrossRefGoogle Scholar
  21. 21.
    Verma VS, Jha RK, Ojha A (2015) Digital watermark extraction using support vector machine with principal component analysis based feature reduction. J Vis Commun Image Represent 31:75–85CrossRefGoogle Scholar
  22. 22.
    Wong PW, Memon N (2001) Secret and public key image watermarking schemes for image authentication and ownership verification. IEEE Trans Image Process 10(10):1593–1601CrossRefzbMATHGoogle Scholar
  23. 23.
    Yang CW, Shen JJ (2010) Recover the tampered image based on VQ indexing. Signal Process 90(1):331–343CrossRefzbMATHGoogle Scholar
  24. 24.
    Yeung MM, Mintzer F (1997) An invisible watermarking technique for image verification. In Image Processing, 1997. Proceedings, International Conference on (Vol. 2, pp 680–683). IEEEGoogle Scholar
  25. 25.
    Zhang Z, Sun H, Gao S, Jin S (2018) Self-recovery reversible image watermarking algorithm. PLoS One 13(6):e0199143CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Electronics and CommunicationPDPM Indian Institute of Information Technology Design and ManufacturingJabalpurIndia

Personalised recommendations