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)

Abstract

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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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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