Distortion-Free Data Embedding for Images

  • Miroslav Goljan
  • Jessica J. Fridrich
  • Rui Du
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2137)


One common drawback of virtually all current data embedding methods is the fact that the original image is inevitably distorted by some small amount of noise due to data embedding itself. This distortion typically cannot be removed completely due to quantization, bit-replacement, or truncation at the grayscales 0 and 255. Although the distortion is often quite small, it may not be acceptable for medical imagery (for legal reasons) or for military images inspected under unusual viewing conditions (after filtering or extreme zoom). In this paper, we introduce a general approach for high-capacity data embedding that is distortion-free (or lossless) in the sense that after the embedded information is extracted from the stego-image, we can revert to the exact copy of the original image before the embedding occurred. The new method can be used as a powerful tool to achieve a variety of non-trivial tasks, including distortion-free robust watermarking, distortion-free authentication using fragile watermarks, and steganalysis. The proposed concepts are also extended to lossy image formats, such as the JPG.


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  1. 1.
    Fridrich, J., Goljan, M., Du, R.: Invertible Authentication. In: Proc. SPIE, Security and Watermarking of Multimedia Contents, San Jose, California January (2001)Google Scholar
  2. 2.
    Fridrich, J., Du, R., Long, M.: Steganalysis of LSB Encoding in Color Images. In: Proc. ICME 2000, New York City, New York, July (2000)Google Scholar
  3. 3.
    Fridrich, J., Goljan, M., Du, R.: Invertible Authentication Watermark for JPEG Files. In: Proc. ITCC, Las Vegas, Nevada, April (2001)Google Scholar
  4. 4.
    Fridrich, J., Goljan, M., Du, R.: Reliable Detection of LSB Steganography in Grayscale and Color Images, in preparation for the ACM Special Session on Multimedia Security and Watermarking, Ottawa, Canada, October 5, 2001.Google Scholar
  5. 5.
    Honsinger, C. W., Jones, P., Rabbani, M., Stoffel, J. C: Lossless Recovery of an Original Image Containing Embedded Data. US Patent application, Docket No:77102/E-D(1999)Google Scholar
  6. 6.
    Honsinger, C. W.: A Robust Data Hiding Technique Based on Convolution with a Randomized Phase Carrier. In: Proc. of PICS’00, Portland, Oregon, March (2000)Google Scholar
  7. 7.
    Macq, B.: Lossless Multiresolution Transform for Image Authenticating Watermarking. In: Proc. of EUSIPCO, Tampere, Finland, September (2000)Google Scholar
  8. 8.
    Sayood, K.: Introduction to Data Compression. Morgan Kaufmann Publishers, San Francisco, California (1996) 87–94MATHGoogle Scholar
  9. 9.
    Westfeld, A. and Pfitzmann, A.: Attacks on Steganographic Systems. In: Proc. 3rd Information Hiding Workshop, Dresden, Germany, September (1999) 61–75Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2001

Authors and Affiliations

  • Miroslav Goljan
    • 1
  • Jessica J. Fridrich
    • 2
  • Rui Du
    • 1
  1. 1.Dept. of Electrical EngineeringSUNY BinghamtonBinghamton
  2. 2.Center for Intelligent SystemsSUNY BinghamtonBinghamton

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