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A wavelet-based particle swarm optimization algorithm for digital image watermarking

Authors:

Jasni Mohamad Zain,

Mohammad Masroor Ahmed,

Ahmed N. Abdalla,

Wang JingAuthors Info & Claims

Integrated Computer-Aided Engineering, Volume 19, Issue 1

Pages 81 - 91

https://doi.org/10.3233/ICA-2012-0392

Published: 01 January 2012 Publication History

Abstract

Digital watermarking techniques have been proposed for copyright protection and multimedia data authentication. The achieved tradeoffs from these techniques between imperceptibility and robustness are always controversial. This paper proposes the application of Discrete Wavelet Transform DWT into image watermarking by using Particle Swarm Optimization PSO which is an evolutionary technique with the stochastic, population-based algorithm for solving this problem. To protect copyright information of digital images, the original image is decomposed according to two-dimensional discrete wavelet transform. Subsequently the preprocessed watermark with an affined scrambling transform is optimal embedded into the vertical subband HL_{m} coefficients in wavelet domain without compromising the quality of the image. In the optimal process, the scaling factors are trained with the assistance of PSO. Furthermore, a novel algorithmic framework is proposed via a forecasted feasibility of the approach to parameters evaluation of hypothesized watermarked images in DWT domain. Simulation results show that the proposed watermarking procedure has better performances in imperceptibility and robustness under various distortions in the comparison of the previous scheme.

References

[1]

H. Adeli and H. Kim, Wavelet-Hybrid Feedback Least Mean Square Algorithm for Robust Control of Structures, Journal of Structural Engineering 130(1) (2004), 128-137.

[2]

H. Adeli, S. Ghosh-Dastidar and N. Dadmehr, A Spatiotemporal Wavelet-Chaos Methodology for EEG-based Diagnosis of Alzheimer's Disease, Neuroscience Letters 444(2) (2008), 190-194.

[3]

M. Ahmadlou and H. Adeli, Wavelet-Synchronization Methodology: A New Approach for EEG-based Diagnosis of ADHD, Clinical EEG and Neuroscience 41(1) (2010), 1-10.

[4]

A. Ahmadlou, H. Adeli and A. Adeli, Fractality and a Wavelet-Chao Methodology for EEG-based Diagnosis of Alzheimer's Disease, Alzheimer Disease and Associated Disorders 25(1) (2011), 85-92.

[5]

M. Al-khassaweneh, H. Al-zoubi and S. Aviyente, The multibit watermarking method for speech signals in the timefrequency domain, Integrated Computer-Aided Engineering 17(1) (2010), 59-67.

[6]

H.O. Altun, A. Orsdemir, G. Sharma and M.F. Bocko, Optimal spread spectrum watermark embedding via a multistep feasibility formulation, IEEE Trans Image Process, 371-387, 2009.

Digital Library

[7]

V. Aslantas, An optimal robust digital image watermarking based on SVD using differential evolution algorithm, Optics Communications 282 (2009), 769-777.

[8]

D. Bratton and J. Kennedy, Defining a Standard for Particle Swarm Optimization, Swarm Intelligence Symposium (2007), 120-127.

Digital Library

[9]

I.J. Cox, J. Kilian, F.T. Leighton and T. Shamoon, Secure spread spectrum watermarking for multimedia, IEEE Trans Image Processing (1997), 1673-1687.

[10]

I.J. Cox and M.L. Miller, The first 50 years of electronic watermarking, EURASIP J Appl Signal Processing (2002), 126-132.

[11]

S. Ghosh-Dastidar and H. Adeli, Neural Network-Wavelet Micro-Simulation Model for Delay and Queue Length Estimation at Freeway Work Zones, Journal of Transportation Engineering 132(4) (2006), 331-341.

[12]

M.S. Hsieh, D.C. Tseng and Y.H. Huang, Hiding Digital Watermarks Using Multiresolution Wavelet Transform, IEEE Transactions on Industrial Electronics (2001), 875-882.

[13]

H. Inoue, A. Miyazaki and T. Katsura, A digital watermark for images using the wavelet transform, Integrated Computer-Aided Engineering 7(2) (2000), 105-115.

Digital Library

[14]

X. Jiang and H. Adeli, Dynamic Fuzzy Wavelet Neuroemulator for Nonlinear Control of Irregular Highrise Building Structures, International Journal for Numerical Methods in Engineering 74(7) (2008), 1045-1066.

[15]

X. Jiang and H. Adeli, Pseudospectra, MUSIC, and Dynamic Wavelet Neural Network for Damage Detection of Highrise Buildings, International Journal for Numerical Methods in Engineering 71(5) (2007), 606-629.

[16]

L. Jing, F. Liu and B. Liu, Robust Image Watermarking Scheme with General Regression Neural Network and FCM Algorithm, Lecture Notes in Computer Science (2008), 243- 250.

[17]

J. Kennedy, R.C. Eberhart and Y. Shi, Swarm Intelligence, Morgan Kaufmann, San Francisco, 2001.

Digital Library

[18]

H. Kim and H. Adeli, Hybrid Control of Smart Structures Using a Novel Wavelet-Based Algorithm, Computer-Aided Civil and Infrastructure Engineering 20(1) (2005), 7-22.

[19]

S. Krbz, Y. Yaslan and B. Gunsel, Robust audio watermark decoding by nonlinear classification, European Signal Processing Conference (2005), 4-8.

[20]

Z.J. Lee, S.W. Lin, S.F. Su and C.Y. Lin, A hybrid watermarking technique applied to digital images, Applied Soft Computing (2008), 798-808.

[21]

D. Lee, T. Kim, S. Lee and J. Paik, Genetic algorithm-based watermarking in discrete wavelet transform domain, Lecture Notes in Computer Science (2006), 709-716.

[22]

X. Li and J. Wang, A steganographic method based upon JPEG and particle swarm optimization algorithm, Information Sciences 177(15) (2007), 3099-3109.

Digital Library

[23]

S. Lyu and H. Farid, Detecting Hidden Messages Using Higher-Order Statistics and Support Vector Machines, Lecture Notes in Computer Science (2002), 340-354.

[24]

D.R. Newbould, L.D. Irby, J.D. Carothers, J.J. Rodriguez and W.T. Holman, Mixed signal design watermarking for IP protection, Integrated Computer-AidedEngineering 10(3) (2003), 249-265.

Digital Library

[25]

R. Shen, Y. Fu and H. Lu, A novel image watermarking scheme based on support vector regression, J Syst Software (2005), 1-8.

[26]

M.D. Swanson, M. Kobayashi, and A.H. Tewfik, Multimedia data-embedding andwatermarking technologies, Proc of IEEE (1998), 1064-1087.

[27]

H. Tao, J.M. Zain and A.N. Abdalla, Particle Swarm Optimization for Digital Image Watermarking, Communications in Computer and Information Science (2010), 1-8.

[28]

Z. Wang and A.C. Bovik, A Universal Image Quality Index, IEEE Signal Processing Letters (2002), 81-84.

[29]

Y.R. Wang, W.H. Lin and L. Yang, An intelligent watermarking method based on particle swarm optimization, Expert Systems with Applications 38(7) (2011), 8024-8029.

Digital Library

[30]

Z. Wang, X. Sun and D. Zhang, A Novel Watermarking Scheme Based on PSO Algorithm, Lecture Notes in Computer Science (2007), 307-314.

[31]

X. Wen, H. Zhang, X. Xu and J. Quan, A new watermarking approach based on probabilistic neural network in wavelet domain, Soft Comput (2009), 355-360.

[32]

Q. Yuan, H. Yao, W. Gao and S. Joo, Blind watermarking method based on DWT middle frequency pair. Proc, IEEE Intl Conf Multimedia Expo (2002), 473-476.

[33]

J.M. Zain, A.M. Fauzi and A.A. Aziz, Clinical Evaluation on Watermarked Medical Images, Proc EMBS 28th Annual International Conference of the IEEE (2006), 5459-5462.

[34]

J.M. Zain and A.M. Fauzi, Evaluation of Medical Image Watermarking with Tamper Detection and Recovery, The 29th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (2007), 5661-5664.

Cited By

Bordel BAlcarria RRobles T(2022)Lightweight encryption for short-range wireless biometric authentication systems in Industry 4.0Integrated Computer-Aided Engineering10.3233/ICA-21067329:2(153-173)Online publication date: 1-Jan-2022
https://dl.acm.org/doi/10.3233/ICA-210673
Bei YZhu XZhang QQiao S(2022)A Robust Image Watermarking Algorithm Based on Content Authentication and Intelligent OptimizationProceedings of the 5th International Conference on Control and Computer Vision10.1145/3561613.3561639(164-170)Online publication date: 19-Aug-2022
https://dl.acm.org/doi/10.1145/3561613.3561639
Sisaudia VVishwakarma V(2021)Copyright protection using KELM-PSO based multi-spectral image watermarking in DCT domain with local texture information based selectionMultimedia Tools and Applications10.1007/s11042-020-10028-y80:6(8667-8688)Online publication date: 1-Mar-2021
https://dl.acm.org/doi/10.1007/s11042-020-10028-y
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A wavelet-based particle swarm optimization algorithm for digital image watermarking
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Published In

cover image Integrated Computer-Aided Engineering

Integrated Computer-Aided Engineering Volume 19, Issue 1

Anniversary Volume: Celebrating 20 Years of Excellence

January 2012

105 pages

ISSN:1069-2509

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IOS Press

Netherlands

Publication History

Published: 01 January 2012

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Cited By

Bordel BAlcarria RRobles T(2022)Lightweight encryption for short-range wireless biometric authentication systems in Industry 4.0Integrated Computer-Aided Engineering10.3233/ICA-21067329:2(153-173)Online publication date: 1-Jan-2022
https://dl.acm.org/doi/10.3233/ICA-210673
Bei YZhu XZhang QQiao S(2022)A Robust Image Watermarking Algorithm Based on Content Authentication and Intelligent OptimizationProceedings of the 5th International Conference on Control and Computer Vision10.1145/3561613.3561639(164-170)Online publication date: 19-Aug-2022
https://dl.acm.org/doi/10.1145/3561613.3561639
Sisaudia VVishwakarma V(2021)Copyright protection using KELM-PSO based multi-spectral image watermarking in DCT domain with local texture information based selectionMultimedia Tools and Applications10.1007/s11042-020-10028-y80:6(8667-8688)Online publication date: 1-Mar-2021
https://dl.acm.org/doi/10.1007/s11042-020-10028-y
(2018)Towards recent developments in the field of digital image forgery detectionInternational Journal of Computer Applications in Technology10.1504/IJCAT.2018.09406458:1(1-16)Online publication date: 1-Jan-2018
https://dl.acm.org/doi/10.1504/IJCAT.2018.094064
(2018)Computational intelligence approaches for classification of medical dataNeurocomputing10.1016/j.neucom.2017.01.126276:C(2-22)Online publication date: 7-Feb-2018
https://dl.acm.org/doi/10.1016/j.neucom.2017.01.126
Wright JJordanov I(2017)Quantum inspired evolutionary algorithms with improved rotation gates for real-coded synthetic and real world optimization problemsIntegrated Computer-Aided Engineering10.3233/ICA-17054524:3(203-223)Online publication date: 1-Jan-2017
https://dl.acm.org/doi/10.3233/ICA-170545
Zeinali YStory B(2017)Competitive probabilistic neural networkIntegrated Computer-Aided Engineering10.3233/ICA-17054024:2(105-118)Online publication date: 1-Jan-2017
https://dl.acm.org/doi/10.3233/ICA-170540
(2016)New methodology for modal parameters identification of smart civil structures using ambient vibrations and synchrosqueezed wavelet transformEngineering Applications of Artificial Intelligence10.1016/j.engappai.2015.10.00548:C(1-12)Online publication date: 1-Feb-2016
https://dl.acm.org/doi/10.1016/j.engappai.2015.10.005
Amezquita-Sanchez JAdeli H(2015)A new music-empirical wavelet transform methodology for time-frequency analysis of noisy nonlinear and non-stationary signalsDigital Signal Processing10.5555/2822911.282293445:C(55-68)Online publication date: 1-Oct-2015
https://dl.acm.org/doi/10.5555/2822911.2822934
Cheng JZhang GCaraffini FNeri F(2015)Multicriteria adaptive differential evolution for global numerical optimizationIntegrated Computer-Aided Engineering10.3233/ICA-15048122:2(103-107)Online publication date: 1-Apr-2015
https://dl.acm.org/doi/10.3233/ICA-150481
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