Fragile Watermarking with Self-recovery Capability via Absolute Moment Block Truncation Coding

Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10039)

Abstract

In this paper, we propose a fragile image watermarking scheme based on Absolute Moment Block Truncation Coding (AMBTC) and self-embedding. According to the constructed binary map and two reconstruction levels, each non-overlapping block in original image can be compressed with the AMBTC algorithm. Then, after scrambling, the compression codes are extended through a random matrix, which can introduce more redundancy into the reference bits to be embedded for content recovery. Also, the relationship between each image block and each reference bit is built so that the recoverable area for tampered image can be increased. Experimental results demonstrate the effectiveness of the proposed scheme.

Keywords

Fragile watermarking AMBTC Tampering detection Content recovery 

References

  1. 1.
    Chang, C., Hu, Y., Lu, T.: A watermarking-based image ownership and tampering authentication scheme. Pattern Recogn. Lett. 27(5), 439–446 (2006)CrossRefGoogle Scholar
  2. 2.
    Xia, Z., Wang, X., Sun, X., Wang, Q.: A secure and dynamic multi-keyword ranked search scheme over encrypted cloud data. IEEE Trans. Parallel Distrib. Syst. 27(2), 340–352 (2015)MathSciNetCrossRefGoogle Scholar
  3. 3.
    Fu, Z., Ren, K., Shu, J., Sun, X., Huang, F.: Enabling personalized search over encrypted outsourced data with efficiency improvement. IEEE Trans. Parallel Distrib. Syst. (2015). doi:10.1109/TPDS.2015.2506573 Google Scholar
  4. 4.
    Fu, Z., Sun, X., Liu, Q., Zhou, L., Shu, J.: achieving efficient cloud search services: multi-keyword ranked search over encrypted cloud data supporting parallel computing. IEICE Trans. Commun. E98-B(1), 190–200 (2015)CrossRefGoogle Scholar
  5. 5.
    Xia, Z., Wang, X., Sun, X., Wang, B.: Steganalysis of least significant bit matching using multi-order differences. Secur. Commun. Netw. 7(8), 1283–1291 (2014)CrossRefGoogle Scholar
  6. 6.
    Xia, Z., Wang, X., Sun, X., Liu, Q., Xiong, N.: Steganalysis of LSB matching using differences between nonadjacent pixels. Multimedia Tools Appl. 75(4), 1947–1962 (2016)CrossRefGoogle Scholar
  7. 7.
    Lin, P., Hsieh, C., Huang, P.: A hierarchical digital watermarking method for image tamper detection and recovery. Pattern Recogn. 38(12), 2519–2529 (2005)CrossRefGoogle Scholar
  8. 8.
    Lee, T., Lin, S.: Dual watermark for image tamper detection and recovery. Pattern Recogn. 41(11), 3497–3506 (2008)CrossRefMATHGoogle Scholar
  9. 9.
    Zhang, X., Wang, S., Qian, Z., Feng, G.: Reference sharing mechanism for watermark self-embedding. IEEE Trans. Image Process. 20(2), 485–495 (2011)MathSciNetCrossRefGoogle Scholar
  10. 10.
    Tsou, C., Hu, Y., Chang, C.: Efficient optimal pixel grouping schemes for AMBTC. Imaging Sci. J. 56(4), 217–231 (2008)CrossRefGoogle Scholar
  11. 11.
    Wang, Z., Bovik, A., Sheikh, H., Simoncelli, E.: Image quality assessment: from error visibility to structural similarity. IEEE Trans. Image Process. 13(4), 600–612 (2004)CrossRefGoogle Scholar
  12. 12.
    Yang, C., Shen, J.: Recover the tampered image based on VQ indexing. Sig. Process. 90, 331–343 (2010)CrossRefMATHGoogle Scholar

Copyright information

© Springer International Publishing AG 2016

Authors and Affiliations

  1. 1.Guangxi Key Lab of Multi-source Information Mining and SecurityGuangxi Normal UniversityGuilinChina
  2. 2.School of Optical-Electrical and Computer EngineeringUniversity of Shanghai for Science and TechnologyShanghaiChina

Personalised recommendations