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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:
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A. A., M. A. and A. A., Crypto-watermarking of transmitted medical images, Journal of Digital Imaging, 26-38. Google Scholar

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A. M. Abbas, Block-based svd image watermarking in spatial and transform domains, International Journal of Electronics, 102 (2015), 1091-1113.   Google Scholar

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A. M. AbdelhakimH. I. Saleh and A. M. Nassar, Quality metric-based fitness function for robust watermarking optimisation with bees algorithm, Iet Image Processing, 10 (2016), 247-252.   Google Scholar

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M. Andalibi and D. M. Chandler, Digital image watermarking via adaptive logo texturization, IEEE Transactions on Image Processing, 24 (2015), 5060-5073.   Google Scholar

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X. D., C. H. K. and Z. H. Y., A joint image encryption and watermarking algorithm based on compressive sensing and chaotic map, Chinese Physics B, 24 (2015), 198-206. Google Scholar

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Y. GuoB. Z. Li and N. Goel, Optimised blind image watermarking method based on firefly algorithm in dwt-qr transform domain, Iet Image Processing, 11 (2017), 406-415.   Google Scholar

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W. H. D., L. Y. F. and S. T., An image quality assessment method using human visual characteristics, 567-573. Google Scholar

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C. J., Research on digital watermarking algorithm based on compressed sensing, in Bulletin of Science and Technology, 11 (2016), 137-141. Google Scholar

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S. LiuZ. Pan and H. Song, Digital image watermarking method based on dct and fractal encoding, Iet Image Processing, 11 (2017), 815-821.   Google Scholar

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R. R. A. Lubis, Analisis kombinasi algoritma watermarking modified least significant bit dengan least significant bit +1, Critical Care, 14 (2015), 1-1.   Google Scholar

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L. NarkedamillyV. P. Evani and S. K. Samayamantula, Discrete multiwavelet--based video watermarking scheme using surf, Etri Journal, 37 (2015), 595-605.   Google Scholar

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K. PraveenM. Sethumadhavan and R. Krishnan, Visual cryptographic schemes using combined boolean operations, Journal of Discrete Mathematical Sciences & Cryptography, 20 (2017), 413-437.  doi: 10.1080/09720529.2015.1086067.  Google Scholar

[14]

Z. QuZ. ChengM. Luo and W. Liu, A robust quantum watermark algorithm based on quantum log-polar images, International Journal of Theoretical Physics, 56 (2017), 3460-3476.  doi: 10.1007/s10773-017-3512-6.  Google Scholar

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K. S. E., Science teachers' conceptualizations and implications for the development of the professional development programs, Eurasia Journal of Mathematics Science and Technology Education, 13 (2017), 3301-3314. Google Scholar

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B. Tenner, Discrete mathematics and theoretical computer science, Discrete Mathematics and Theoretical Computer Science, 369-382. Google Scholar

[18]

M. A. Ting, D. P. Gao and N. T. Chen, Optimization and simulation of anti-attack method for composite color digital watermark image, Computer Simulation, 418-422. Google Scholar

[19]

D. C. WangC. C. TianB. J. Chen and Y. H. Tian, Dual watermarking for color images based on 4d quaternion frequency domain, Journal of Jilin University, 45 (2015), 1336-1346.   Google Scholar

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Y. WangJ. LiuY. YangD. Ma and R. Liu, 3d model watermarking algorithm robust to geometric attacks, Iet Image Processing, 11 (2017), 822-832.   Google Scholar

show all references

References:
[1]

A. A., M. A. and A. A., Crypto-watermarking of transmitted medical images, Journal of Digital Imaging, 26-38. Google Scholar

[2]

A. M. Abbas, Block-based svd image watermarking in spatial and transform domains, International Journal of Electronics, 102 (2015), 1091-1113.   Google Scholar

[3]

A. M. AbdelhakimH. I. Saleh and A. M. Nassar, Quality metric-based fitness function for robust watermarking optimisation with bees algorithm, Iet Image Processing, 10 (2016), 247-252.   Google Scholar

[4]

M. Andalibi and D. M. Chandler, Digital image watermarking via adaptive logo texturization, IEEE Transactions on Image Processing, 24 (2015), 5060-5073.   Google Scholar

[5]

X. D., C. H. K. and Z. H. Y., A joint image encryption and watermarking algorithm based on compressive sensing and chaotic map, Chinese Physics B, 24 (2015), 198-206. Google Scholar

[6]

Y. GuoB. Z. Li and N. Goel, Optimised blind image watermarking method based on firefly algorithm in dwt-qr transform domain, Iet Image Processing, 11 (2017), 406-415.   Google Scholar

[7]

W. H. D., L. Y. F. and S. T., An image quality assessment method using human visual characteristics, 567-573. Google Scholar

[8]

C. J., Research on digital watermarking algorithm based on compressed sensing, in Bulletin of Science and Technology, 11 (2016), 137-141. Google Scholar

[9]

S. LiuZ. Pan and H. Song, Digital image watermarking method based on dct and fractal encoding, Iet Image Processing, 11 (2017), 815-821.   Google Scholar

[10]

R. R. A. Lubis, Analisis kombinasi algoritma watermarking modified least significant bit dengan least significant bit +1, Critical Care, 14 (2015), 1-1.   Google Scholar

[11]

L. MaoW. GuiwuF. AlsaadiT. Hayat and A. Alsaedi, Bipolar 2-tuple linguistic aggregation operators in multiple attribute decision making, Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology, 33 (2017), 1197-1207.   Google Scholar

[12]

L. NarkedamillyV. P. Evani and S. K. Samayamantula, Discrete multiwavelet--based video watermarking scheme using surf, Etri Journal, 37 (2015), 595-605.   Google Scholar

[13]

K. PraveenM. Sethumadhavan and R. Krishnan, Visual cryptographic schemes using combined boolean operations, Journal of Discrete Mathematical Sciences & Cryptography, 20 (2017), 413-437.  doi: 10.1080/09720529.2015.1086067.  Google Scholar

[14]

Z. QuZ. ChengM. Luo and W. Liu, A robust quantum watermark algorithm based on quantum log-polar images, International Journal of Theoretical Physics, 56 (2017), 3460-3476.  doi: 10.1007/s10773-017-3512-6.  Google Scholar

[15]

K. S. E., Science teachers' conceptualizations and implications for the development of the professional development programs, Eurasia Journal of Mathematics Science and Technology Education, 13 (2017), 3301-3314. Google Scholar

[16]

L. B. Si, Regional cooperation efficiency evaluation of equipment manufacturing industry based on dea method: Empirical analysis of beijing-tianjin-hebei region and yangtze river delta region, Journal of Interdisciplinary Mathematics, 20 (2017), 281-293.   Google Scholar

[17]

B. Tenner, Discrete mathematics and theoretical computer science, Discrete Mathematics and Theoretical Computer Science, 369-382. Google Scholar

[18]

M. A. Ting, D. P. Gao and N. T. Chen, Optimization and simulation of anti-attack method for composite color digital watermark image, Computer Simulation, 418-422. Google Scholar

[19]

D. C. WangC. C. TianB. J. Chen and Y. H. Tian, Dual watermarking for color images based on 4d quaternion frequency domain, Journal of Jilin University, 45 (2015), 1336-1346.   Google Scholar

[20]

Y. WangJ. LiuY. YangD. Ma and R. Liu, 3d model watermarking algorithm robust to geometric attacks, Iet Image Processing, 11 (2017), 822-832.   Google Scholar

Figure 1.  Image digital watermarking preprocessing under virtual reality technology
Figure 2.  Color images of the original carrier
Figure 3.  Original watermark image and scrambled watermark image
Figure 4.  Watermarked color image
Figure 5.  Watermarking effects and watermarking extraction effects after different attacks
Table 1.  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
Table 2.  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
Table 3.  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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