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      Color Image Blind Watermarking Algorithm Based on QR Decomposition and Voting in DWT Domain

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      https://www.riss.kr/link?id=A102653573

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      다국어 초록 (Multilingual Abstract)

      To achieve a better trade-off between robustness and imperceptibility, a blind watermarking algorithm based on QR decomposition and voting for color image in DWT domain is proposed in the paper. Most of the existing QR decomposition based watermarking...

      To achieve a better trade-off between robustness and imperceptibility, a blind watermarking algorithm based on QR decomposition and voting for color image in DWT domain is proposed in the paper. Most of the existing QR decomposition based watermarking schemes take the first row of R matrix into consideration while in our approach the watermark is embedded by modifying the first column element of Q matrix. In the embedding process, DCT is applied to the R, G and B color components, respectively. Then DWT is utilized on the DCT coefficients of each component and acquire corresponding LL, HL, LH, and HH. Later, the associated DWT coefficients in LH and HH are decomposed with QR decomposition and the watermark message is embedded into the first column of Q matrix by changing Q21 and Q31 with stable characteristic. In the extraction phase, a redundant watermark scheme with voting method is used to improve the robustness of the watermarking algorithm. Experimental results show that the proposed algorithm, compared with the existing methods is robust enough to resist common signal attacks including filtering, noising, small cutting and JPEG compressing.

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      목차 (Table of Contents)

      • Abstract
      • 1. Introduction
      • 2. Related Techniques
      • 2.1. Discrete Wavelet Transform
      • 2.2. QR Decomposition
      • Abstract
      • 1. Introduction
      • 2. Related Techniques
      • 2.1. Discrete Wavelet Transform
      • 2.2. QR Decomposition
      • 3. Watermark Embedding and Extracting Algorithm
      • 3.1. Watermark Embedding Algorithm
      • 3.2. Watermark Extraction Algorithm
      • 4. Experimental Results
      • 4.1 Imperceptibility Analysis
      • 4.2 Robustness Analysis
      • 5. Conclusion
      • References
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