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A Digital Watermarking Scheme Based on Singular Value Decomposition

This presentation introduces a novel digital watermarking scheme based on Singular Value Decomposition (SVD) for embedding binary logos into images. It covers the digital watermarking system's components, different watermarking categories, and the proposed SVD-based scheme. Experimental results demonstrate the proposed scheme's effectiveness in terms of robustness and efficiency, with high Peak Signal-to-Noise Ratios (PSNR) above 31 dB. The scheme involves embedding one bit in three different image blocks through a secured process that includes a one-way hash function based on Rabin’s scheme. The embedding process is detailed along with the extracting process, showcasing successful watermark retrieval even through image modifications like compression, sharpening, blurring, cropping, and noise addition. Comparison with other schemes validates the efficiency of this SVD-based watermarking approach.

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A Digital Watermarking Scheme Based on Singular Value Decomposition

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  1. A Digital Watermarking Scheme Based on Singular Value Decomposition Speaker: Prof. Chin-Chen Chang

  2. Outline • Digital Watermarking System • Watermarking Category • SVD (Singular Value Decomposition) • Proposed Scheme • Experimental Results • Conclusions

  3. Digital Watermarking System

  4. Watermarking Category- Robustness • Three categories • Robust watermarking schemes • Fragile watermarking schemes • Semi-fragile watermarking schemes 

  5. Watermarking Category- embedding approach • Spatial domain-based scheme • Low computational complexity • Lower robustness • Frequency domain-based scheme • Need more computation • Provide better robustness

  6. • SVD-based schemes • Similar to frequency domain based scheme • SVD can be considered as a transformation

  7. SVD • Singular Value Decomposition • Assume that rank of A is r. • U and V are N x N orthogonal matrices, U x UT=I, V x VT=I • S is an N x N diagonal matrix, σ1 ≥σ2 ≥…≥σr ≥σr+1 =…=σN =0

  8. Proposed Scheme (1/3) 4 1 0 0 1 1 0 0 1 1 0 1 0 1 1 0 0 0 1 0 1 1 0 1 0 4 Binary watermarking image One bit needs to be embedded in three different blocks Original image Use a one way hash function based on Rabin’s scheme to decide the embedding block

  9. 3.2527 3.2527+δxWi Proposed Scheme (2/3) • Embedding process Wi = 1, δ = 20 SVD 23.2527 U x x VT

  10. The same process 18.6047-5.4539 =13.1508 > 10 W’1=1 W’1+W’2+W’3 > 2 W’2=0 W’=1 W’2=1 Proposed Scheme (3/3) • Extracting process δ/2 = 10 SVD U x x VT

  11. Experimental Results (1/7) • Seven 512x512 gray-scale test images and one 64x64 binary image

  12. Two measurements • PSNR • Peak Signal-to-Noise Ratio • BCR • Bit Correction Ratio

  13. Experimental Results (2/7)

  14. Original image Watermarked image (PSNR = 35.37dB) Extracted watermark Bit Correction Ratio = 100%

  15. Experimental Results (3/7)

  16. Watermarked image after JPEG compressing (PSNR = 35.87dB) Extracted watermark (Bit Correction Ratio = 87.92%)

  17. Experimental Results (4/7)

  18. Watermarked image after sharpening process (PSNR = 29.23dB) Extracted watermark (Bit Correction Ratio = 95.73%)

  19. Experimental Results (5/7)

  20. Watermarked image after blurring process (PSNR = 35.60dB) Extracted watermark (Bit Correction Ratio = 92.41%)

  21. Experimental Results (6/7)

  22. Watermarked image after cropping process (PSNR = 35.60dB) Extracted watermark (Bit Correction Ratio = 90.19%)

  23. Experimental Results (7/7)

  24. Watermarked image after adding noise (PSNR = 32.54dB) Extracted watermark (Bit Correction Ratio = 89.28%)

  25. Comparisons with other schemes

  26. Conclusion • SVD-based watermarking scheme for binary logo • The proposed scheme has good efficiency • The PSNR values of the watermarked images are all greater than 31 dB

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