A feature-based robust digital image watermarking scheme

Chih Wei Tang*, Hsueh-Ming Hang

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

304 Scopus citations

Abstract

A robust digital image watermarking scheme that combines image feature extraction and image normalization is proposed. The goal is to resist both geometric distortion and signal processing attacks. We adopt a feature extraction method called Mexican Hat wavelet scale interaction. The extracted feature points can survive a variety of attacks and be used as reference points for both watermark embedding and detection. The normalized image of an image (object) is nearly invariant with respect to rotations. As a result, the watermark detection task can be much simplified when it is applied to the normalized image. However, because image normalization is sensitive to image local variation, we apply image normalization to nonoverlapped image disks separately. The disks are centered at the extracted feature points. Several copies of a 16-bit watermark sequence are embedded in the original image to improve the robustness of watermarks. Simulation results show that our scheme can survive low-quality JPEG compression, color reduction, sharpening, Gaussian filtering, median filtering, row or column removal, shearing, rotation, local warping, cropping, and linear geometric transformations.

Original languageEnglish
Pages (from-to)950-959
Number of pages10
JournalIEEE Transactions on Signal Processing
Volume51
Issue number4
DOIs
StatePublished - 1 Apr 2003

Keywords

  • Feature extraction
  • Geometric distortion
  • Image normalization
  • Marr wavelet
  • Robust watermark

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