Multimedia Systems

, Volume 9, Issue 2, pp 121–130

Robust image authentication using content based compression

  • Ee-Chien Chang
  • Mohan S. Kankanhalli
  • Xin Guan
  • Zhiyong Huang
  • Yinghui Wu
Original Paper

DOI: 10.1007/s00530-003-0083-6

Cite this article as:
Chang, EC., Kankanhalli, M.S., Guan, X. et al. Multimedia Systems (2003) 9: 121. doi:10.1007/s00530-003-0083-6
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Abstract.

Image authentication is becoming very important for certifying data integrity. A key issue in image authentication is the design of a compact signature that contains sufficient information to detect illegal tampering yet is robust under allowable manipulations. In this paper, we recognize that most permissible operations on images are global distortions like low-pass filtering and JPEG compression, whereas illegal data manipulations tend to be localized distortions. To exploit this observation, we propose an image authentication scheme where the signature is the result of an extremely low-bit-rate content-based compression. The content-based compression is guided by a space-variant weighting function whose values are higher in the more important and sensitive region. This spatially dependent weighting function determines a weighted norm that is particularly sensitive to the localized distortions induced by illegal tampering. It also gives a better compactness compared to the usual compression schemes that treat every spatial region as being equally important. In our implementation, the weighting function is a multifovea weighted function that resembles the biological foveated vision system. The foveae are salient points determined in the scale-space representation of the image. The desirable properties of multifovea weighted function in the wavelet domains fit nicely into our scheme. We have implemented our technique and tested its robustness and sensitivity for several manipulations.

Keywords:

Digital signature Security Watermarking Signal processing Wavelets 

Copyright information

© Springer-Verlag Berlin/Heidelberg 2003

Authors and Affiliations

  • Ee-Chien Chang
    • 1
  • Mohan S. Kankanhalli
    • 1
  • Xin Guan
    • 2
  • Zhiyong Huang
    • 1
  • Yinghui Wu
    • 1
  1. 1.Department of Computer Science, Computational ScienceNational University of SingaporeSingapore
  2. 2.Department of Computational ScienceNational University of SingaporeSingapore

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