Radon Transform-Based Secure Image Hashing

  • Dung Q. Nguyen
  • Li Weng
  • Bart Preneel
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7025)


This paper presents a robust and secure image hash algorithm. The algorithm extracts robust image features in the Radon transform domain. A randomization mechanism is designed to achieve good discrimination and security. The hash value is dependent on a secret key. We evaluate the performance of the proposed algorithm and compare the results with those of one existing Radon transform-based algorithm. We show that the proposed algorithm has good robustness against content-preserving distortion. It withstands JPEG compression, filtering, noise addition as well as moderate geometrical distortions. Additionally, we achieve improved performance in terms of discrimination, sensitivity to malicious tampering and receiver operating characteristics. We also analyze the security of the proposed algorithm using differential entropy and confusion/diffusion capabilities. Simulation shows that the proposed algorithm well satisfies these metrics.


JPEG Compression Hash Algorithm Feature Extraction Stage Secure Image Rotation Detection 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


  1. 1.
    Venkatesan, R., Koon, S., Jakubowski, M., Moulin, P.: Robust image hashing. In: Proceedings of IEEE International Conference on Image Processing, vol. 3, pp. 664–666 (2000)Google Scholar
  2. 2.
    Swaminathan, A., Mao, Y., Wu, M.: Robust and secure image hashing. IEEE Transactions on Information Forensics and Security 1(2) (June 2006) Google Scholar
  3. 3.
    Mihçak, M.K., Venkatesan, R.: New iterative geometric methods for robust perceptual image hashing. In: Sander, T. (ed.) DRM 2001. LNCS, vol. 2320, pp. 13–21. Springer, Heidelberg (2002)CrossRefGoogle Scholar
  4. 4.
    Lefebvre, F., Macq, B., Legat, J.: Rash: Radon soft hash algorithm. In: Proceedings of the European Signal Processing Conference, Toulouse, France (September 2002)Google Scholar
  5. 5.
    Fridrich, J., Goljan, M.: Robust hash functions for digital watermarking. In: Proceedings of the International Conference on Information Technology: Coding and Computing (2000)Google Scholar
  6. 6.
    Coskun, B., Memon, N.: Confusion/diffusion capabilities of some robust hash functions. In: Proceedings of 40th Annual Conference on Information Sciences and Systems (2006)Google Scholar
  7. 7.
    Mao, Y., Wu, M.: Unicity distance of robust image hashing. IEEE Transactions on Information Forensics and Security 2(3) (September 2007)Google Scholar

Copyright information

© IFIP International Federation for Information Processing 2011

Authors and Affiliations

  • Dung Q. Nguyen
    • 1
  • Li Weng
    • 1
  • Bart Preneel
    • 1
  1. 1.Katholieke Universiteit Leuven, ESAT/COSIC-IBBTBelgium

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