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Semantic Watermarking in Image Processing for Enhanced Robustness

This paper discusses hidden digital watermarks in images using a DCT-domain watermarking system. The system emphasizes good perceptual invisibility, acceptable robustness, and user-selected options. Watermarks are permuted for spatial relationship spreading and embedded in the host image's DCT domain. The algorithm provides advantages like fast processing and robustness against JPEG compression, while considering image block effects. The scheme also allows the embedding of watermark blocks based on signal pixels and embedding positions within each block. Reversible pseudo-random permutation and polarity reversing techniques are employed for watermark extraction.

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Semantic Watermarking in Image Processing for Enhanced Robustness

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  1. DCT-Domain WatermarkingChiou-Ting Hsu and Ja-Ling Wu, "Hidden digital watermarks in images," IEEE Trans. On Image Processing, vol. 8, No. 1, January 1999 Multimedia Security

  2. Requirements Invisibility Robustness No ambiguity Embedding Comparison Extraction A generic image watermarking system • Distortions • Image processing • Compression • …... Watermark Watermark

  3. Advantages of this scheme • Advantages: • Semantically meaningful watermark pattern • Good perceptual invisibility • Acceptable robustness • Various user-selected options • Reasonable complexity/execution time

  4. System overview • Watermarks are randomly permuted to spread their spatial relationship, and then embedded in the DCT domain of the host image, with consideration of invisibility/robustness

  5. Block Diagrams of the Original Algorithm Original Image Watermark Image FDCT Pseudo-random Permutation Block-based Mapping Embedding (Polarity Reversing) IDCT Watermarked Image

  6. Block Diagrams of the Original Algorithm Original Image Suspected Image FDCT FDCT Extract the Permutated Data (XOR) Reverse Block-based Permutation Reverse Pseudo-random Permutation Extracted Watermark

  7. Block DCT/IDCT • Advantages • Fast • Suitable for robustness against JPEG compression • Disadvantages • Block effect • Effect of picture cropping

  8. Semantic Meaningful Watermarks • Watermarks can be verified with naked eyes by understanding the semantics of the extracted watermark patterns The seal of CML (in Chinese characters)

  9. Pseudo-Random Permutation • A n-bit Linear Feedback Shift Register (LFSR) is used to generate the maximal length (2n-1) sequence Original Watermark Permuted Watermark The 14-bit Shift Register that permutes 1-16384

  10. Block-based Mapping • Watermark blocks with more signal pixels are embedded into image blocks with higher variances • to achieve better perceptual invisibility.

  11. Choices of embedding positions within each block: Low-frequency Bad invisibility High-frequency Bad robustness => Middle-frequency Fix positions in each block Embedding(1/2) Embedding 4 watermark pixels

  12. Embedding(2/2) • Polarity: the inequalityrelations between the scaled DC value and the selected AC coefficients • Effects of the JPEGquantization table are also considered

  13. Polarity Reversing • Polarity: the inequality relationship between DC & corresponding AC values within each DCT block. watermark bits: 0 1 0 1 0 0 1 polarity: 1 1 0 0 1 0 1 XOR 1 0 0 1 1 0 0 reversed polarity: Embedding Extraction

  14. Extraction • Exclusive-or (XOR) operations are performed on the two polarity patterns to obtain the permuted binary data.

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