Skip to main content
SpringerLink
Log in

Superpixel-Based Watermarking Scheme for Image Authentication and Recovery

  • Conference paper
  • First Online:
Digital-Forensics and Watermarking (IWDW 2014)

Part of the book series: Lecture Notes in Computer Science ((LNSC,volume 9023))

Included in the following conference series:

Abstract

Based on the superpixel segmentation mechanism, a novel fragile watermarking scheme for image authentication and recovery is proposed. For each superpixel region, the authentication watermark is generated by putting the pixels into a feedback-based chaotic system and embedded into the region itself. The content of each superpixel is compressed to construct the recovery watermark, which is embedded into another selected superpixel. To extract the authentication and recovery watermark properly, the superpixel boundaries are marked. The reliability of a superpixel is first determined by its authentication watermark. To improve detection accuracy, the recovery watermark extracted from authentic superpixels is utilized for precise detection. Moreover, the recovery information extracted from authentic superpixels is decompressed to recover the tampered regions. Experimental results demonstrate that the proposed method can not only resist general counterfeiting attacks, especially vector quantization (VQ) attack, but also has an excellent performance on location accuracy and self-recovery.

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

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

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

    Article  Google Scholar 

  2. Wong, P.W.: A public key watermark for image verication and authentication. In: Proceedings of the IEEE International Conference on Image Processing, Chicago, IL, pp. 425–429, October 1998

    Google Scholar 

  3. Holliman, M., Memon, N.: Counterfeiting attacks on oblivious block-wise independent invisible watermarking schemes. IEEE Trans. Image Process. 9(3), 432–441 (2000)

    Article  Google Scholar 

  4. Celik, M.U., Sharma, G., Saber, E., Tekalp, A.M.: Hierarchical watermarking for secure image authentication with localization. IEEE Trans. Image Process. 11(6), 585–595 (2002)

    Article  Google Scholar 

  5. Suthaharan, S., Kim, S.: A gradient image dependent fragile watermarking for improved security and localization. In: Proceedings of the IEEE Southeast Con, pp. 343–348 (2004)

    Google Scholar 

  6. Chen, W.C., Wang, M.S.: A fuzzy c-means clustering-based fragile watermarking scheme for image authentication. Expert Syst. Appl. 36(2), 1300–1307 (2009)

    Article  Google Scholar 

  7. Lin, P.L., Hsieh, C.K., Huang, P.W.: A hierarchical digital watermarking method for image tamper detection and recovery. Pattern Recogn. 38(12), 2519–2529 (2005)

    Article  Google Scholar 

  8. Li, C., Wang, Y., Ma, B., Zhang, Z.: A novel self-recovery fragile watermarking scheme based on dual-redundant-ring structure. Comput. Electr. Eng. 37, 927–940 (2011)

    Article  Google Scholar 

  9. He, H., Chen, F., Huo, Y.: Self-embedding fragile watermarking scheme combined average with VQ encoding. In: Shi, Y.Q., Kim, H.-J., Pérez-González, F. (eds.) IWDW 2012. LNCS, vol. 7809, pp. 120–134. Springer, Heidelberg (2013)

    Chapter  Google Scholar 

  10. Ren, X., Malik, J.: Learning a classifacation model for segmentation. In: ICCV 2003, pp. 10–17. IEEE Computer Society (2003)

    Google Scholar 

  11. Fulkerson, B., Vedali, A., Soatto, S.: Class segmentation and object localization with superpixel neighborhoods. In: ICCV 2009, pp. 670–677. IEEE (2009)

    Google Scholar 

  12. Wang, Z., Feng, J., Xi, H.: Image classification via object-aware holistic superpixel selection. IEEE Trans. Image Process. 22(11), 4341–4352 (2013)

    Article  MathSciNet  Google Scholar 

  13. Yang, F., Lu, H., Yang, M.-H.: Robust superpixel tracking. IEEE Trans. Image Process. 23(4), 1639–1651 (2014)

    Article  MathSciNet  Google Scholar 

  14. Levinshtein, A.S., Kutulakos, K.N., Fleet, D.J., Dickinson, S.J., Siddiqi, K.: Turbopixels: fast superpixels using geometric flows. IEEE Trans. Pattern Anal. Mach. Intell. 31(12), 2290–2297 (2009)

    Article  Google Scholar 

  15. Ni, R., Ruan, Q.: Neighbor-aided authentication watermarking based on a chaotic system with feedback. IEICE Trans. Inf. Syst. E91-D(8), 2196–2198 (2008)

    Article  Google Scholar 

  16. Braga-Neto, U., Goutsias, J.: A theoretical tour of connectivity in image processing and analysis. J. Math. Image Vis. 19(1), 5–31 (2003)

    Article  MATH  MathSciNet  Google Scholar 

Download references

Acknowledgements

This work is supported in part by 973 Program (2011CB302204), National Natural Science Funds for Distinguished Young Scholar (61025013), National NSF of China (61332012, 61272355), PCSIRT (IRT 201206), and Open Projects Program of National Laboratory of Pattern Recognition (201306309).

Author information

Authors and Affiliations

  1. Institute of Information Science, Beijing Key Laboratory of Advanced Information Science and Network Technology, Beijing Jiaotong University, Beijing, 100044, China

    Xiumei Qiao, Rongrong Ni & Yao Zhao

Authors
  1. Xiumei Qiao
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Rongrong Ni
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Yao Zhao
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding authors

Correspondence to Rongrong Ni or Yao Zhao .

Editor information

Editors and Affiliations

  1. NJIT, Newark, New Jersey, USA

    Yun-Qing Shi

  2. Korea University, Seoul, Korea, Republic of (South Korea)

    Hyoung Joong Kim

  3. Universidad de La Laguna, La Laguna, Spain

    Fernando Pérez-González

  4. Department of Computer Science and Information Engineering, National Dong Hwa University, Hualien, Taiwan

    Ching-Nung Yang

Rights and permissions

Reprints and permissions

Copyright information

© 2015 Springer International Publishing Switzerland

About this paper

Cite this paper

Qiao, X., Ni, R., Zhao, Y. (2015). Superpixel-Based Watermarking Scheme for Image Authentication and Recovery. In: Shi, YQ., Kim, H., Pérez-González, F., Yang, CN. (eds) Digital-Forensics and Watermarking. IWDW 2014. Lecture Notes in Computer Science(), vol 9023. Springer, Cham. https://doi.org/10.1007/978-3-319-19321-2_12

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-19321-2_12

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-19320-5

  • Online ISBN: 978-3-319-19321-2

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation