TY - JOUR
T1 - Dynamic multi-watermarking and detecting in DWT domain
AU - Gao, Youcai
AU - Wang, Jinwei
AU - Shi, Yun Qing
N1 - Funding Information:
Acknowledgements This work was jointly supported by the National Natural Science Foundation of China (Grant nos. 61772281, 61502241, 61272421, 61232016, 61402235, and 61572258), and the Priority Academic Program Development of Jiangsu Higher Education Institutions and CICAEET.
PY - 2019/6/1
Y1 - 2019/6/1
N2 - Dynamic multi-watermarking embeds watermarks into the same region of a cover imperceptibly by simultaneously using different embedding rules. It is regarded as a solution to protect the cover’s copyright or track illegal distributors. Till now, few works have been done on multi-watermarking, especially dynamic multi-watermarking. In this paper, a novel dynamic multi-watermarking rule is proposed, which embeds different watermarks into DWT coefficients controlled by two secret keys, i.e., the sign control key and the factor control key. Two types of the corresponding dynamic multi-watermarking detectors, i.e., optimum and locally optimum, are derived based on the generalized Gaussian distribution and NP criterion. The robustness of the proposed scheme is analyzed using the optimal Lagrange algorithm, which aims to obtain optimal embedding strength factors. Experimental results verify the prominence of the proposed scheme and the validity of theoretical analysis.
AB - Dynamic multi-watermarking embeds watermarks into the same region of a cover imperceptibly by simultaneously using different embedding rules. It is regarded as a solution to protect the cover’s copyright or track illegal distributors. Till now, few works have been done on multi-watermarking, especially dynamic multi-watermarking. In this paper, a novel dynamic multi-watermarking rule is proposed, which embeds different watermarks into DWT coefficients controlled by two secret keys, i.e., the sign control key and the factor control key. Two types of the corresponding dynamic multi-watermarking detectors, i.e., optimum and locally optimum, are derived based on the generalized Gaussian distribution and NP criterion. The robustness of the proposed scheme is analyzed using the optimal Lagrange algorithm, which aims to obtain optimal embedding strength factors. Experimental results verify the prominence of the proposed scheme and the validity of theoretical analysis.
KW - Additive rule
KW - Dynamic detector
KW - Dynamic multi-watermarking rule
KW - Multiplicative rule
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U2 - 10.1007/s11554-018-0812-x
DO - 10.1007/s11554-018-0812-x
M3 - Article
AN - SCOPUS:85051869034
SN - 1861-8200
VL - 16
SP - 565
EP - 576
JO - Journal of Real-Time Image Processing
JF - Journal of Real-Time Image Processing
IS - 3
ER -