American Institute of Mathematical Sciences

Advanced
December  2015, 8(6): 1291-1299. doi: 10.3934/dcdss.2015.8.1291

Characteristic analysis of carrier based on the filtering and a multi-wavelet method for the information hiding

Shuai Ren 1, , Tao Zhang 2, and  Fangxia Shi 3,

1. 

School of Information Engineering, Chang'an University, Xi'an, Shaanxi 710064, China
2. 

School of Electronic and Control Engineering, Chang'an University, Xi'an, Shaanxi 710064, China
3. 

School of Information Engineering, Xizang Minzu University, Xianyang, Shaanxi 712082, China

Received  June 2015 Revised  September 2015 Published  December 2015

The characteristic consistency between the original and the stego carriers is an important indicator to evaluate an information hiding algorithm. Different from the traditional carrier pre-processing methods which are based on the operation domains, we propose a characteristics analysis-based preprocessing scheme. We use the Gaussian pyramid filtering and CARDBAL2 multi-wavelet transform to analyze the energy characteristics of the carrier, so the original carrier can be decomposed into several sub-regions with different energy level. And at the same time, the processed carrier shows us the redundancy space structurally through the combination bit plane method, which can provide some invisible hiding positions. Obviously, the energy and structure characteristics are at least related with the robustness and invisibility of the hiding result respectively. So we can improve these performances compared with the traditional methods. At the same time, some optimization theories like the Chebyshev map are used to improve other performances. At last, the experimental shows the achievements of this scheme in the form of data.
Keywords: Gaussian pyramid, genetic algorithm., Information hiding, CARDBAL2 multi-wavelet transform, Chebyshev map.
Mathematics Subject Classification: Primary: 94A62, 68Q30; Secondary: 94A0.
Citation: Shuai Ren, Tao Zhang, Fangxia Shi. Characteristic analysis of carrier based on the filtering and a multi-wavelet method for the information hiding. Discrete & Continuous Dynamical Systems - S, 2015, 8 (6) : 1291-1299. doi: 10.3934/dcdss.2015.8.1291
References:
[1]

A. Basu, A. Saha, J. Das, S. Roy, S. Mitra and I. Mal, On the implementation of a digital watermarking based on phase congruency,, Advances in Intelligent Systems & Computing, 328 (2014), 113.  doi: 10.1007/978-3-319-12012-6_13.  Google Scholar

[2]

L. Cui and W. Li, Adaptive multiwavelet-based watermarking through JPW masking,, IEEE Transactions on Image Processing, 20 (2011), 1047.  doi: 10.1109/TIP.2010.2079551.  Google Scholar

[3]

A. Durdek, S. R. Jensen and J. Juselius, et al., Adaptive order polynomial algorithm in a multiwavelet representation scheme,, Applied Numerical Mathematics, 92 (2015), 40.  doi: 10.1016/j.apnum.2014.12.006.  Google Scholar

[4]

K. Jafari-Khouzani, Multiwavelet grading of pathological images of prostate,, IEEE Trans. Biomed. Eng., 50 (2003), 697.  doi: 10.1109/TBME.2003.812194.  Google Scholar

[5]

J. Kim, M. Yi and M. S. Obaidat, Advanced computer mathematics based cryptography and security technologies,, International Journal of Computer Mathematics, 90 (2013), 2512.  doi: 10.1080/00207160.2013.868728.  Google Scholar

[6]

Y. Kutlu, Feature extraction for ECG heartbeats using higher order statistics of WPD coefficients,, Comput. Methods Programs Biomed., 105 (2012), 257.  doi: 10.1016/j.cmpb.2011.10.002.  Google Scholar

[7]

Y. Li, H. L. Wei and S. A. Billings, Identification of time-varying systems using multi-wavelet basis functions,, Control Systems Technology IEEE Transactions on, 19 (2011), 656.  doi: 10.1109/TCST.2010.2052257.  Google Scholar

[8]

X. B. Ren, An optimal image thresholding using genetic algorithm,, Proceedings of the 2009 International Forum on Computer Science-Technology and Applications, 1 (2009), 169.  doi: 10.1109/IFCSTA.2009.48.  Google Scholar

[9]

B. Stoyanov and K. Kordov, Novel image encryption scheme based on chebyshev polynomial and duffing map,, The Scientific World Journal, 2014 (2014).  doi: 10.1155/2014/283639.  Google Scholar

[10]

M. Saini and R. Chhikara, Performance evaluation of DCT and DWT features for blind image steganalysis using neural networks,, International Journal of Computer Applications, 114 (2015), 20.  doi: 10.5120/19974-1868.  Google Scholar

[11]

A. R. Tate, N. Beloff and A. R. Balques, et al., Exploiting the potential of large databases of electronic health records for research using rapid search algorithms and an intuitive query interface,, Applied Numerical Mathematics, 21 (2014), 292.  doi: 10.1136/amiajnl-2013-001847.  Google Scholar

[12]

L. Yang, J. Lv and Y. Xiang, Underdetermined blind source separation by parallel factor analysis in time-frequency domain,, Cognitive Computation, 5 (2013), 207.  doi: 10.1007/s12559-012-9177-9.  Google Scholar

[13]

T. Zhang, D. J. Mu and S. Ren, A confidential communication-oriented information hiding algorithm based on GHM multi-wavelet and DCT,, Applied Mathematics & Information Sciences, 7 (2013), 1803.  doi: 10.12785/amis/070518.  Google Scholar

show all references

References:
[1]

A. Basu, A. Saha, J. Das, S. Roy, S. Mitra and I. Mal, On the implementation of a digital watermarking based on phase congruency,, Advances in Intelligent Systems & Computing, 328 (2014), 113.  doi: 10.1007/978-3-319-12012-6_13.  Google Scholar

[2]

L. Cui and W. Li, Adaptive multiwavelet-based watermarking through JPW masking,, IEEE Transactions on Image Processing, 20 (2011), 1047.  doi: 10.1109/TIP.2010.2079551.  Google Scholar

[3]

A. Durdek, S. R. Jensen and J. Juselius, et al., Adaptive order polynomial algorithm in a multiwavelet representation scheme,, Applied Numerical Mathematics, 92 (2015), 40.  doi: 10.1016/j.apnum.2014.12.006.  Google Scholar

[4]

K. Jafari-Khouzani, Multiwavelet grading of pathological images of prostate,, IEEE Trans. Biomed. Eng., 50 (2003), 697.  doi: 10.1109/TBME.2003.812194.  Google Scholar

[5]

J. Kim, M. Yi and M. S. Obaidat, Advanced computer mathematics based cryptography and security technologies,, International Journal of Computer Mathematics, 90 (2013), 2512.  doi: 10.1080/00207160.2013.868728.  Google Scholar

[6]

Y. Kutlu, Feature extraction for ECG heartbeats using higher order statistics of WPD coefficients,, Comput. Methods Programs Biomed., 105 (2012), 257.  doi: 10.1016/j.cmpb.2011.10.002.  Google Scholar

[7]

Y. Li, H. L. Wei and S. A. Billings, Identification of time-varying systems using multi-wavelet basis functions,, Control Systems Technology IEEE Transactions on, 19 (2011), 656.  doi: 10.1109/TCST.2010.2052257.  Google Scholar

[8]

X. B. Ren, An optimal image thresholding using genetic algorithm,, Proceedings of the 2009 International Forum on Computer Science-Technology and Applications, 1 (2009), 169.  doi: 10.1109/IFCSTA.2009.48.  Google Scholar

[9]

B. Stoyanov and K. Kordov, Novel image encryption scheme based on chebyshev polynomial and duffing map,, The Scientific World Journal, 2014 (2014).  doi: 10.1155/2014/283639.  Google Scholar

[10]

M. Saini and R. Chhikara, Performance evaluation of DCT and DWT features for blind image steganalysis using neural networks,, International Journal of Computer Applications, 114 (2015), 20.  doi: 10.5120/19974-1868.  Google Scholar

[11]

A. R. Tate, N. Beloff and A. R. Balques, et al., Exploiting the potential of large databases of electronic health records for research using rapid search algorithms and an intuitive query interface,, Applied Numerical Mathematics, 21 (2014), 292.  doi: 10.1136/amiajnl-2013-001847.  Google Scholar

[12]

L. Yang, J. Lv and Y. Xiang, Underdetermined blind source separation by parallel factor analysis in time-frequency domain,, Cognitive Computation, 5 (2013), 207.  doi: 10.1007/s12559-012-9177-9.  Google Scholar

[13]

T. Zhang, D. J. Mu and S. Ren, A confidential communication-oriented information hiding algorithm based on GHM multi-wavelet and DCT,, Applied Mathematics & Information Sciences, 7 (2013), 1803.  doi: 10.12785/amis/070518.  Google Scholar

[1]

Xueyan Wu. An algorithm for reversible information hiding of encrypted medical images in homomorphic encrypted domain. Discrete & Continuous Dynamical Systems - S, 2019, 12 (4&5) : 1441-1455. doi: 10.3934/dcdss.2019099
[2]

Daniel Fusca. The Madelung transform as a momentum map. Journal of Geometric Mechanics, 2017, 9 (2) : 157-165. doi: 10.3934/jgm.2017006
[3]

P. Cerejeiras, M. Ferreira, U. Kähler, F. Sommen. Continuous wavelet transform and wavelet frames on the sphere using Clifford analysis. Communications on Pure & Applied Analysis, 2007, 6 (3) : 619-641. doi: 10.3934/cpaa.2007.6.619
[4]

T. W. Leung, Chi Kin Chan, Marvin D. Troutt. A mixed simulated annealing-genetic algorithm approach to the multi-buyer multi-item joint replenishment problem: advantages of meta-heuristics. Journal of Industrial & Management Optimization, 2008, 4 (1) : 53-66. doi: 10.3934/jimo.2008.4.53
[5]

Ömer Oruç, Alaattin Esen, Fatih Bulut. A unified finite difference Chebyshev wavelet method for numerically solving time fractional Burgers' equation. Discrete & Continuous Dynamical Systems - S, 2019, 12 (3) : 533-542. doi: 10.3934/dcdss.2019035
[6]

Jianbin Yang, Cong Wang. A wavelet frame approach for removal of mixed Gaussian and impulse noise on surfaces. Inverse Problems & Imaging, 2017, 11 (5) : 783-798. doi: 10.3934/ipi.2017037
[7]

C. Bonanno, G. Menconi. Computational information for the logistic map at the chaos threshold. Discrete & Continuous Dynamical Systems - B, 2002, 2 (3) : 415-431. doi: 10.3934/dcdsb.2002.2.415
[8]

Chihiro Matsuoka, Koichi Hiraide. Special functions created by Borel-Laplace transform of Hénon map. Electronic Research Announcements, 2011, 18: 1-11. doi: 10.3934/era.2011.18.1
[9]

Yaw Chang, Lin Chen. Solve the vehicle routing problem with time windows via a genetic algorithm. Conference Publications, 2007, 2007 (Special) : 240-249. doi: 10.3934/proc.2007.2007.240
[10]

Didem Cinar, José António Oliveira, Y. Ilker Topcu, Panos M. Pardalos. A priority-based genetic algorithm for a flexible job shop scheduling problem. Journal of Industrial & Management Optimization, 2016, 12 (4) : 1391-1415. doi: 10.3934/jimo.2016.12.1391
[11]

Abdel-Rahman Hedar, Alaa Fahim. Filter-based genetic algorithm for mixed variable programming. Numerical Algebra, Control & Optimization, 2011, 1 (1) : 99-116. doi: 10.3934/naco.2011.1.99
[12]

Ji Zhang, Hongxia Lv, Boer Deng, Wenxian Wang. An adaptive genetic algorithm for solving the optimization model of car flow organizat. Discrete & Continuous Dynamical Systems - S, 2018, 0 (0) : 0-0. doi: 10.3934/dcdss.2020200
[13]

Anatoli F. Ivanov. On global dynamics in a multi-dimensional discrete map. Conference Publications, 2015, 2015 (special) : 652-659. doi: 10.3934/proc.2015.0652
[14]

Sanming Liu, Zhijie Wang, Chongyang Liu. Proximal iterative Gaussian smoothing algorithm for a class of nonsmooth convex minimization problems. Numerical Algebra, Control & Optimization, 2015, 5 (1) : 79-89. doi: 10.3934/naco.2015.5.79
[15]

Shi Yan, Jun Liu, Haiyang Huang, Xue-Cheng Tai. A dual EM algorithm for TV regularized Gaussian mixture model in image segmentation. Inverse Problems & Imaging, 2019, 13 (3) : 653-677. doi: 10.3934/ipi.2019030
[16]

Justyna Jarczyk, Witold Jarczyk. Gaussian iterative algorithm and integrated automorphism equation for random means. Discrete & Continuous Dynamical Systems - A, 2019, 0 (0) : 0-0. doi: 10.3934/dcds.2020135
[17]

Luigi Ambrosio, Federico Glaudo, Dario Trevisan. On the optimal map in the $ 2 $-dimensional random matching problem. Discrete & Continuous Dynamical Systems - A, 2019, 39 (12) : 7291-7308. doi: 10.3934/dcds.2019304
[18]

Abderrazek Karoui. A note on the construction of nonseparable wavelet bases and multiwavelet matrix filters of $L^2(\R^n)$, where $n\geq 2$. Electronic Research Announcements, 2003, 9: 32-39.

[19]

Huyuan Chen, Dong Ye, Feng Zhou. On gaussian curvature equation in $ \mathbb{R}^2 $ with prescribed nonpositive curvature. Discrete & Continuous Dynamical Systems - A, 2019, 0 (0) : 0-0. doi: 10.3934/dcds.2020125
[20]

Xiaojing Ye, Haomin Zhou. Fast total variation wavelet inpainting via approximated primal-dual hybrid gradient algorithm. Inverse Problems & Imaging, 2013, 7 (3) : 1031-1050. doi: 10.3934/ipi.2013.7.1031

2018 Impact Factor: 0.545

Tools

Metrics

  • PDF downloads (21)
  • HTML views (0)
  • Cited by (0)

Other articles
by authors

[Back to Top]

Copyright © 2020 American Institute of Mathematical Sciences