A Robust Watermarking Algorithm Based on Blob-Harris and NSCT-Zernike

Tianqi ZHANG; Lin ZHOU; Xianming LIANG; Wei XU

doi:10.11999/JEIT200164

Volume 43 Issue 7

Jul. 2021

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Article Navigation > Journal of Electronics & Information Technology > 2021 > 43(7): 2038-2045

Tianqi ZHANG, Lin ZHOU, Xianming LIANG, Wei XU. A Robust Watermarking Algorithm Based on Blob-Harris and NSCT-Zernike[J]. Journal of Electronics & Information Technology, 2021, 43(7): 2038-2045. doi: 10.11999/JEIT200164

Citation:

Tianqi ZHANG, Lin ZHOU, Xianming LIANG, Wei XU. A Robust Watermarking Algorithm Based on Blob-Harris and NSCT-Zernike[J]. Journal of Electronics & Information Technology, 2021, 43(7): 2038-2045. doi: 10.11999/JEIT200164

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A Robust Watermarking Algorithm Based on Blob-Harris and NSCT-Zernike

doi: 10.11999/JEIT200164

1.
School of Communication and Information Engineering, Chongqing Key Laboratory of Signal and Information Processing (CQKLS&IP), Chongqing University of Posts and Telecommunications (CQUPT), Chongqing 400065, China
2.
Southwest China Institute of Electronic Technology, Chengdu 610036, China

Funds: The National Natural Science Foundation of China (61701067, 61771085, 61671095, 61702065), The Project of Key Laboratory of Signal and Information Processing of Chongqing (CSTC2009CA2003), The Chongqing Graduate Research and Innovation Project (CYS19248), The Research Project of Chongqing Educational Commission(KJ1600427, KJ1600429)

Received Date: 2020-03-10
Rev Recd Date: 2020-11-30

Available Online: 2020-12-05

Publish Date: 2021-07-10

Abstract

Abstract

To resist the geometric attack of watermarked images effectively, a robust watermarking algorithm based on Blob-Harris feature region combined with NonSubsampled Contourlet Transform (NSCT) and pseudo Zernike moment is proposed. First, the original image is extracted from its low-frequency image after two-layer NSCT. Then, Blob-Harris detection operator is used to extract the feature points of the low-frequency image. The feature regions are determined according to the feature scale of each feature point, and the stable non-overlapping feature areas are optimized and filtered out and zero padding around them to obtain square feature areas as watermark embedding areas. Finally, the Zernike moments of each square feature area are calculated, the watermarking information is embeded to quantized modulation regularized Zernike moments. The experimental results show that when the peak signal-to-noise ratio of the Lena reaches more than 40 dB, the algorithm has relatively strong robustness to conventional image processing, geometric attacks such as scaling, rotation, and shearing and combined attacks.
- Watermarking,
- Feature region,
- NonSubsampled Contourlet Transform(NSCT),
- Pseudo-Zernike moment

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References(17)

References

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