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August & September  2019, 12(4&5): 1427-1440. doi: 10.3934/dcdss.2019098

## Research on image digital watermarking optimization algorithm under virtual reality technology

 1 Language Laboratory, Department of Foreign Languages, Anhui Jianzhu University, Hefei, China 2 Department of Foreign Languages, Anhui Jianzhu University, Hefei, China

* Corresponding author: Yi Zhang

Received  July 2017 Revised  December 2017 Published  November 2018

Aiming at the shortcomings of current algorithms due to the fixed steps, which is easy to fall into local optimum, with robustness and poor transparency, and cannot be balanced against various common attacks, an optimization algorithm of digital image watermarking algorithm based on Drosophila was proposed. In the support of the virtual reality technology, the original color host image was transformed from the RGB space to YCrCb space, and the pixel block of the Y component was divided into a certain size; according to the principle of forming DC coefficients in the DCT domain, the DC coefficient of each block is calculated directly in the airspace, and the amount of modification for each DC coefficient is determined based on the watermark information and the quantization step size; according to the distribution characteristics of DC coefficient, watermarks are embedded directly in the airspace; the type of digital watermarking and digital watermarking pretreatment methods were determined by using Drosophila optimization algorithm. At the same time, digital watermark embedding, extraction rules and initial steps were selected and identified. The Drosophila optimization algorithm with step size reduces the balance between global and local search ability, which makes up for the shortcomings of traditional algorithm. The experimental results showed that the proposed algorithm can effectively balance the invisibility and robustness of the watermark, and can resist all kinds of common attacks, which with a better visual extraction effect.

Citation: Yi Zhang, Xiao-Li Ma. Research on image digital watermarking optimization algorithm under virtual reality technology. Discrete & Continuous Dynamical Systems - S, 2019, 12 (4&5) : 1427-1440. doi: 10.3934/dcdss.2019098
##### References:

show all references

##### References:
Image digital watermarking preprocessing under virtual reality technology
Color images of the original carrier
Original watermark image and scrambled watermark image
Watermarked color image
Watermarking effects and watermarking extraction effects after different attacks
PSNR values of the original and watermarked images for each attack
 Attack mode Figure 4 (a) Figure 4 (b) No attack 86.4859 87.0142 Rotation (5 degrees) 72.6435 73.8816 Image scaling (1/2) 77.5878 75.3243 JPEG compression (90) 83.6266 84.1118 Cropping 62.5677 64.2054
 Attack mode Figure 4 (a) Figure 4 (b) No attack 86.4859 87.0142 Rotation (5 degrees) 72.6435 73.8816 Image scaling (1/2) 77.5878 75.3243 JPEG compression (90) 83.6266 84.1118 Cropping 62.5677 64.2054
NC value of the original watermark and extracted watermark image under various attacks
 Attack mode Figure 4 (a) Figure 4 (b) No attack 1.0000 1.0000 Salt and pepper noise (0.05) 0.9987 0.9887 Median filter ($5 \times 5$) 0.9654 0.9574 Rotation (5 degrees) 0.9613 0.9788 Image scaling (1/2) 0.9527 0.9755 JPEG compression (90) 0.9774 0.9802 Cropping 0.9997 1.0000
 Attack mode Figure 4 (a) Figure 4 (b) No attack 1.0000 1.0000 Salt and pepper noise (0.05) 0.9987 0.9887 Median filter ($5 \times 5$) 0.9654 0.9574 Rotation (5 degrees) 0.9613 0.9788 Image scaling (1/2) 0.9527 0.9755 JPEG compression (90) 0.9774 0.9802 Cropping 0.9997 1.0000
Experimental results of two watermarked images under varying degrees of attack
 Attack mode Vector image Figure 2 (a) NC value Figure 2 (b) NC value JPEG compression (quality factor) 90 0.9778 0.9805 70 0.9594 0.9698 50 0.9473 0.9587 30 0.9372 0.9583 Salt and pepper noise (intensity) 0.05 0.9877 0.9886 0.10 0.9602 0.9734 0.15 0.9571 0.9722 0.20 0.9501 0.9579
 Attack mode Vector image Figure 2 (a) NC value Figure 2 (b) NC value JPEG compression (quality factor) 90 0.9778 0.9805 70 0.9594 0.9698 50 0.9473 0.9587 30 0.9372 0.9583 Salt and pepper noise (intensity) 0.05 0.9877 0.9886 0.10 0.9602 0.9734 0.15 0.9571 0.9722 0.20 0.9501 0.9579
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