Skip to main content
SpringerLink
Log in

Perceptual hash function for scalable video

  • Regular Contribution
  • Published:
International Journal of Information Security Aims and scope Submit manuscript

Abstract

Perceptual hash functions are important for video authentication based on digital signature verifying the originality and integrity of videos. They derive hashes from the perceptual contents of the videos and are robust against the common content-preserving operations on the videos. The advancements in the field of scalable video coding call for efficient hash functions that are also robust against the temporal, spatial and bit rate scalability features of the these coding schemes. This paper presents a new algorithm to extract hashes of scalably coded videos using the 3D discrete wavelet transform. A hash of a video is computed at the group-of-frames level from the spatio-temporal low-pass bands of the wavelet-transformed groups-of-frames. For each group-of-frames, the spatio-temporal low-pass band is divided into perceptual blocks and a hash is derived from the cumulative averages of their averages. Experimental results demonstrate the robustness of the hash function against the scalability features and the common content-preserving operations as well as the sensitivity to the various types of content differences. Two critical properties of the hash function, diffusion and confusion, are also examined.

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.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11

Similar content being viewed by others

References

  1. Kalker, T., Haitsma, J., Oostveen, J.: Issues with digital watermarking and perceptual hashing. In: Proceedings of the SPIE Multimedia Systems Appl. IV, Denver, CO. 4518, 189–197 (Aug 2001)

  2. Han, S.-H., Chu, C.-H.: Content-based image authentication: current status, issues and challenges. Springer Int. J. Inf. Secur. 9(1), 19–32 (2010)

    Article  Google Scholar 

  3. Adami, N., Signoroni, A., Leonardi, R.: State-of-the-art and trends in scalable video compression with wavelet-based approaches. IEEE Trans. Circuits Syst. Video Tech. 17(9), 1238–1255 (2007)

    Article  Google Scholar 

  4. Atrey, P.K., Yan, W.Q., Kankanhalli, M.S.: A scalable signature scheme for video authentication. Springer J. Multimed. Tools Appl. 34(1), 107–135 (2007)

    Article  Google Scholar 

  5. Roover, C.D., Vleeschouwer, C.D., Lefebvre, F., Macq, B.: Robust video hashing based on radial projections of key frames. IEEE Trans. Signal Process. 53, 4020–4037 (2005)

    Article  MathSciNet  Google Scholar 

  6. Oostveen, J., Kalker, T., Haitsma, J.: Visual hashing of digital video: applications and techniques. In: Proceedings of the SPIE Application of Digital Image Processing XXIV, San Diego, CA 4472, 121–131 (July/Aug 2001)

  7. Uehara, T., Safavi-Naini, R., Ogunbona, P.: An MPEG tolerant authentication system for video data. In: Proceedings of the IEEE International Conference Multimedia Expo, Taipei, pp. 891–894 (June 2004)

  8. Sun, Q., He, D., Tian, Q.: A secure and robust authentication scheme for video transcoding. IEEE Trans. Circuits Syst. Video Tech. 16(10), 1232–1244 (2006)

    Article  Google Scholar 

  9. Coskun, B., Sankur, B., Memon, N.: Spatio-temporal transform based video hashing. IEEE Trans. Multimed. 8(6), 1190–1208 (2006)

    Article  Google Scholar 

  10. Sun, Q., Chang, S.-F.: A secure and robust digital signature scheme for JPEG2000 image authentication system. IEEE Trans. Multimed. 7(3), 480–494 (2005)

    Article  Google Scholar 

  11. Vetro, A., Christopoulos, C., Sun, H.: Video transcoding architectures and techniques: an overview. IEEE Signal Process. Mag. 20(2), 18–29 (2003)

    Article  Google Scholar 

  12. Kim, B.-J., Xiong, Z., Pearlman, W.A.: Low bit-rate scalable video coding with 3-D set partitioning in hierarchical trees (3-D SPIHT). IEEE Trans. Circuits Syst. Video Tech. 10(8), 1374–1387 (2000)

    Article  Google Scholar 

  13. Danyali, H., Mertins, A.: A fully SNR, spatial and temporal scalable 3DSPIHT-based video coding algorithm for video streaming over heterogeneous networks. In: Proceedings of the IEEE International Conference Convergent Technologies Asia-Pacific Region, Bangalore 4, 1445–1449 (Oct 2003)

  14. Bottreau, V., Benetiere, M., Felts, B., Pesquet-Popescu, B.: A fully scalable 3D subband video codec. In: Proceedings of the IEEE International Conference Image Processing, Thessaloniki, 2, 1017–1020 (July 2001)

  15. Strang, G., Nguyen, T.Q.: Wavelets and Filter Banks. Wellesley-Cambridge Press, MA (1996)

    MATH  Google Scholar 

  16. Coskun, B., Memon, N.: Confusion/ diffusion capabilities of some robust hash functions. In: Proceedings of the IEEE 40th Annual Conference Information Sciences Systems. Princeton, NJ, pp. 1188–1193 (March 2006)

  17. Proakis, J.G., Manolakis, D.G.: Digital Signal Processing: Principles, Algorithms, and Applications. Prentice-Hall, NJ (1996)

    Google Scholar 

  18. Tao, Y., Muthukkumarasamy, V., Verma, B., Blumenstein, M.: A texture feature extraction technique using 2D-DFT and hamming distance. In: Proceedings of the IEEE International Conference on Computational Intelligence Multimedia Applications, Xi’an, pp. 120–125 (Sept 2003)

  19. Dutta, Mazumdar D., Chanda, B.: Digital Image Processing and Analysis. Prentice-Hall of India, New Delhi (2000)

    Google Scholar 

  20. Jain, A.K.: Fundamentals of Digital Image Processing. Englewood Cliffs, NJ (1989)

    MATH  Google Scholar 

  21. Antonini, M., Barlaud, M., Mathieu, P., Daubechies, I.: Image coding using wavelet transform. IEEE Trans. Image Process. 1, 205–220 (1992)

    Article  Google Scholar 

  22. Thiemert, S., Sahbi, H., Steinebach, M.: Using entropy for image and video authentication watermarks. In: Proceeding of the SPIE Security, Steganography, and Watermarking of Multimedia Contents VIII, San Jose, CA 6072, pp. 607218 (Feb 2006)

Download references

Acknowledgments

The authors acknowledge the unanimous reviewers for their valuable suggestions which are included in the paper.

Author information

Authors and Affiliations

  1. Assam Engineering College, Guwahati,  781 013, Assam, India

    Navajit Saikia

  2. Indian Institute of Technology Guwahati, Guwahati, 781 039, Assam, India

    Prabin K. Bora

Authors
  1. Navajit Saikia
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Prabin K. Bora
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Prabin K. Bora.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Saikia, N., Bora, P.K. Perceptual hash function for scalable video. Int. J. Inf. Secur. 13, 81–93 (2014). https://doi.org/10.1007/s10207-013-0211-z

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10207-013-0211-z

Keywords

Search

Navigation