• Previous Article
    Multi-objective optimization algorithm based on improved particle swarm in cloud computing environment
  • DCDS-S Home
  • This Issue
  • Next Article
    An algorithm for reversible information hiding of encrypted medical images in homomorphic encrypted domain
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, doi: 10.3934/dcdss.2019098
References:
[1]

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

[2]

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

[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.

[4]

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

[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.

[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.

[7]

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

[8]

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

[9]

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

[10]

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

[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.

[12]

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

[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.

[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.

[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.

[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.

[17]

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

[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.

[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.

[20]

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

show all references

References:
[1]

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

[2]

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

[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.

[4]

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

[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.

[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.

[7]

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

[8]

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

[9]

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

[10]

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

[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.

[12]

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

[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.

[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.

[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.

[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.

[17]

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

[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.

[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.

[20]

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

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
[1]

Kemal Kilic, Menekse G. Saygi, Semih O. Sezer. Exact and heuristic methods for personalized display advertising in virtual reality platforms. Journal of Industrial & Management Optimization, 2018, 13 (5) : 1-22. doi: 10.3934/jimo.2018073

[2]

Jianjun Zhang, Yunyi Hu, James G. Nagy. A scaled gradient method for digital tomographic image reconstruction. Inverse Problems & Imaging, 2018, 12 (1) : 239-259. doi: 10.3934/ipi.2018010

[3]

Luis C. Corchón, Clara Eugenia García. Technology transfer: Barriers and opportunities. Journal of Dynamics & Games, 2018, 5 (4) : 343-355. doi: 10.3934/jdg.2018021

[4]

Juan Carlos De los Reyes, Carola-Bibiane Schönlieb. Image denoising: Learning the noise model via nonsmooth PDE-constrained optimization. Inverse Problems & Imaging, 2013, 7 (4) : 1183-1214. doi: 10.3934/ipi.2013.7.1183

[5]

Lizhong Peng, Shujun Dang, Bojin Zhuang. Localization operator and digital communication capacity of channel. Communications on Pure & Applied Analysis, 2007, 6 (3) : 819-827. doi: 10.3934/cpaa.2007.6.819

[6]

Joshua Du, Liancheng Wang. Dispersion relations for supersonic multiple virtual jets. Conference Publications, 2011, 2011 (Special) : 381-390. doi: 10.3934/proc.2011.2011.381

[7]

Luca Consolini, Alessandro Costalunga, Manfredi Maggiore. A coordinate-free theory of virtual holonomic constraints. Journal of Geometric Mechanics, 2018, 10 (4) : 467-502. doi: 10.3934/jgm.2018018

[8]

Archana Prashanth Joshi, Meng Han, Yan Wang. A survey on security and privacy issues of blockchain technology. Mathematical Foundations of Computing, 2018, 1 (2) : 121-147. doi: 10.3934/mfc.2018007

[9]

Hiroyuki Torikai. Basic spike-train properties of a digital spiking neuron. Discrete & Continuous Dynamical Systems - B, 2008, 9 (1) : 183-198. doi: 10.3934/dcdsb.2008.9.183

[10]

Sie Long Kek, Mohd Ismail Abd Aziz, Kok Lay Teo. A gradient algorithm for optimal control problems with model-reality differences. Numerical Algebra, Control & Optimization, 2015, 5 (3) : 251-266. doi: 10.3934/naco.2015.5.251

[11]

Božidar Jovanović, Vladimir Jovanović. Virtual billiards in pseudo–euclidean spaces: Discrete hamiltonian and contact integrability. Discrete & Continuous Dynamical Systems - A, 2017, 37 (10) : 5163-5190. doi: 10.3934/dcds.2017224

[12]

Hongming Yang, Dexin Yi, Junhua Zhao, Fengji Luo, Zhaoyang Dong. Distributed optimal dispatch of virtual power plant based on ELM transformation. Journal of Industrial & Management Optimization, 2014, 10 (4) : 1297-1318. doi: 10.3934/jimo.2014.10.1297

[13]

Shunfu Jin, Wuyi Yue, Chao Meng, Zsolt Saffer. A novel active DRX mechanism in LTE technology and its performance evaluation. Journal of Industrial & Management Optimization, 2015, 11 (3) : 849-866. doi: 10.3934/jimo.2015.11.849

[14]

Jianxiong Zhang, Zhenyu Bai, Wansheng Tang. Optimal pricing policy for deteriorating items with preservation technology investment. Journal of Industrial & Management Optimization, 2014, 10 (4) : 1261-1277. doi: 10.3934/jimo.2014.10.1261

[15]

Nikos I. Kavallaris, Andrew A. Lacey, Christos V. Nikolopoulos, Dimitrios E. Tzanetis. On the quenching behaviour of a semilinear wave equation modelling MEMS technology. Discrete & Continuous Dynamical Systems - A, 2015, 35 (3) : 1009-1037. doi: 10.3934/dcds.2015.35.1009

[16]

Muhammad Waqas Iqbal, Biswajit Sarkar. Application of preservation technology for lifetime dependent products in an integrated production system. Journal of Industrial & Management Optimization, 2017, 13 (5) : 1-28. doi: 10.3934/jimo.2018144

[17]

Fei Gao. Data encryption algorithm for e-commerce platform based on blockchain technology. Discrete & Continuous Dynamical Systems - S, 2018, 0 (0) : 1457-1470. doi: 10.3934/dcdss.2019100

[18]

Weiping Li, Haiyan Wu, Jie Yang. Intelligent recognition algorithm for social network sensitive information based on classification technology. Discrete & Continuous Dynamical Systems - S, 2018, 0 (0) : 1385-1398. doi: 10.3934/dcdss.2019095

[19]

Dana Paquin, Doron Levy, Eduard Schreibmann, Lei Xing. Multiscale Image Registration. Mathematical Biosciences & Engineering, 2006, 3 (2) : 389-418. doi: 10.3934/mbe.2006.3.389

[20]

Antoni Buades, Bartomeu Coll, Jose-Luis Lisani, Catalina Sbert. Conditional image diffusion. Inverse Problems & Imaging, 2007, 1 (4) : 593-608. doi: 10.3934/ipi.2007.1.593

2017 Impact Factor: 0.561

Metrics

  • PDF downloads (11)
  • HTML views (68)
  • Cited by (0)

Other articles
by authors

[Back to Top]