Transparent and Robust Audio Watermarking Using Synergy LU Decomposition and the Fibonacci Sequence in GBT-DCT-DWT Transforms

Document Type : Original Article

Authors

1 Faculty of Computer Engineering, NajafAbad Branch, Islamic Azad University, NajafAbad, Iran

2 Department of Computer Engineering, Dezful Branch, Islamic Azad University, Dezful, Iran

Abstract

Digital watermarking technology is presented as one of the best solutions for solving unauthorized copying, content identification and authentication of digital media. Digital watermarking can be applied in the fields of image, text, audio, and video contents. Audio watermarking has recently attracted the attention of researchers because the human auditory system is much more sensitive than his vision system. Therefore, insertion of the data into audio signals in a transparent way is much more difficult than other watermarking species. An efficient audio watermarking system should be able to improve reconciliation of the three measures of transparency, strength and capacitance. Improving the compromise between these three measures is a challenging problem, due to the fact that increasing the capacity of the input signal, causes distortions in the signal which in turn causes a reduction in transparency and robustness. In this paper, a new method is proposed for watermarking of audio signals that is able to improve the three criteria of transparency, robustness and capacity in an appropriate manner. In order to improve the resilience of the hidden  signal against signal processing attacks, the synergy of three efficient transforms in the field of signal processing namely, the graph-centric conversion (GBT), the discrete cosine transform (DCT) and the discrete wavelet transform (DWT), has been used. In addition, in order to maintain the transparency of the watermarked signal, the watermarked data in the high triangle matrix resulting from the LU decomposition of the approximation coefficients of the discrete wavelet are entered in an order which is based on the Fibonacci sequence. The procedure is based on the value of the watermarked bit, the non-zero values ​​of the upper triangular matrix are replaced by the nearest even or odd numbers in the Fibonacci sequence. The latent extraction operation is completely blind. The results of the evaluation of the   proposed method on audio files with Blue, Electronic, Classic and Jazz styles show that the proposed method, despite good resistance to various signal processing attacks, has an average signal rate of 45.13 dB and a placement rate of 625.75 bits per second.
 

Keywords

References

[1]     Petitcolas,  A. P. Fabien,  R.  J. Anderson,  and M. G. Kuhn, “Information  hiding-a survey,” Proceedings of the IEEE 87, no. 7, pp. 1062-1078, 1999.## 
[2]     J. C. Ingemar, Matthew L. Miller, J. A. Bloom, and C. Honsinger, “Digital watermarking,” vol. 1558607145, Springer, 2002.## 
[3]     J. C. Ingemar, Matt L. Miller, and A. L. McKellips,                 “Watermarking as communications with side information,” published in the Proceedings of the IEEE, vol. 87, no. 7, pp. 1127-1141, 1999.## 
[4]     A. Brickman, “Literature survey on audio watermarking,” EE381K-Multidimensional Signal Processing, March 2003.## 
[5]     Arnold M, “Audio Watermarking: features, applications and algorithms,” IEEE International conference Multimedia and Expo, vol. 2, pp. 1033-1066, 2000.## 
[6]     L. Miller Matt, J. C. Ingemar, Jean-Paul, M. G. Linnartz, and Ton Kalker, “A review of watermarking principles and practices,” published in Digital Signal Processing in Multimedia Systems, Ed. K. K.Parhi and T. Nishitani, Marcell Dekker Inc., pp. 461-485, 1999.## 
[7]     S. Prabhishek and R. S. Chadha, “A  Survey  of  Digital Watermarking  Techniques, Applications  and  Attacks,” International  Journal  of  Engineering  and  Innovative Technology  (IJEIT), vol. 2, Issue 9, pp.165-175, 2013.## 
[8]     S. Amit, J. Susheel, and  J. Anurag, “A  Survay: Digital  Video  Watermarking,” International  Journal  of Scientific &  Engineering Research, vol. 4, Issue  7, July- ISSN 2229-5518 pp. 1261- 1265, 2013.## 
[9]     H. Farooq,  “A  Survey  of  Digital  Vatermarking Techniques  for  multimedia  data,” MIT  International Journal  of Electronics  and  communication Engineering, vol. 2, no.1,   ISSN 2230-7672, pp. 37-43, Jan. 2012.## 
[10]  H. T. Hu and L. Y. Hsu, Robust, “Transparent and                high-capacity audio watermarking in DCT domain,” Signal Processing, vol. 109, pp. 226-235, 2015.## 
[11]  S. M. Pourhashemi, M. Mosleh, and Y. Erfani, “Audio watermarking based on synergy between Lucas regular sequence and Fast Fourier Transform,” Multimedia Tools and Applications, vol. 78(16), pp. 22883-22908, 2019.## 
[12]  B. Lei, Y. Soon, and E. L. Tan, “Robust SVD-based audio watermarking scheme with differential evolution optimization,” IEEE transactions on audio, speech, and language processing, vol. 21(11), pp. 2368-2378, 2013.## 
[13]  X. C. Yuan, C. M. Pun, and C. P. Chen, “Robust               Mel-Frequency Cepstral coefficients feature detection and dual-tree complex wavelet transform for digital audio watermarking,” Information Sciences, vol. 298, pp. 159-179, 2015.## 
[14]  H. T. Hu, L. Y. Hsu, and H. H. Chou, “Perceptual-based DWPT-DCT framework for selective blind audio watermarking,” Signal Processing, vol. 105, pp.                 316-327, 2014.## 
[15]  A. Al-Haj, “A dual transform audio watermarking algorithm,” Multimedia tools and applications, vol. 73(3), pp.             1897-1912, 2014.## 
[16]  H. N. Huang, S. T. Chen, M. S. Lin, W. M. Kung, and C. Y. Hsu, “Optimization-based embedding for wavelet-domain audio watermarking,” Journal of Signal Processing Systems, vol. 80(2), pp. 197-208, 2015.## 
[17]  Y. Xiang, I. Natgunanathan, Y. Rong, and S. Guo, “Spread spectrum-based high embedding capacity watermarking method for audio signals,” IEEE/ACM Transactions on Audio, Speech and Language Processing (TASLP), vol. 23(12), pp. 2228-2237, 2015.## 
[18]  H. T. Hu and L. Y. Hsu, “Supplementary Schemes to Enhance the Performance of DWT-RDM Based Blind Audio Watermarking,” Circuits, Systems, and Signal Processing, pp. 1-22, 2016.## 
[19]  M. Jeyhoon, M. Asgari, L. Ehsan, and S. Z. Jalilzadeh, “Blind audio watermarking algorithm based on DCT, linear regression and standard deviation,” Multimedia Tools and Applications, pp. 1-17, 2016.## 
 [20]  M. Mosleh, H. Latifpour, M. Kheyrandish, M. Mosleh, and N. A. Hosseinpour, “robust intelligent audio watermarking scheme using support vector machine,” Journal of Zhejiang UniversitySCIENCE, pp. 11-08, 2016.## 
[21]  R. Li, S. Xu, and H. Yang, “Spread spectrum audio watermarking based on perceptual characteristic aware extraction,” IET Signal Processing, vol. 10(3), pp.             266-273, 2016.## 
[22]  D. Bratić, F. Vešović, and V. Mijanović, “Audio watermarking under gradient-based 37 reconstruction attack,” In Embedded Computing (MECO), 2016 5th Mediterranean Conference on IEEE, pp. 148- 152, 2016.## 
[23]  S. M. Mohsenfar, M. Mosleh, and A. Barati, “Audio watermarking method using QR decomposition and genetic algorithm,” Multimedia Tools and Applications, vol. 74(3), pp. 759-779, 2015.## 
[24]  M. Mosleh, et al., “High-capacity, transparent and robust audio watermarking based on synergy between DCT transform and LU decomposition using genetic algorithm,” Analog Integrated Circuits and Signal Processing, vol. 100(3), pp. 513-525, 2019.## 
[25]  A. A. Attari and A. BeheshtiShirazi, “A. Robust and Blind AudioWatermarking inWavelet Domain,” In: Proceedings of the International Conference on Graphics and Signal Processing - ICGSP ‘17. Singapore, Singapore, pp. 69–73, 2019.## 
[26]  H. Karajeh and M. Maqableh, “An imperceptible, robust, and high payload capacity audio watermarking scheme based on the DCT transformation and Schur decomposition,” Analog Integr Circ Sig Process, 2018.## 
[27]  A. Kaur and M. K. Dutta, “An optimized high payload audio watermarking algorithm based on LU-factorization, Multimedia Systems, vol. 24(3), pp. 341-353, 2018.## 
[28]  M. Farzaneh, R. M. Toroghi, and M. Asgari, “Audio Compression Using Graph- based Transform,” In 2018 9th International Symposium on  Telecommunications (IST), pp. 410-415, 2018.##  
[29]  G. Strng, “The discrete cosine transform,” SIAM Review, vol. 41(1), pp. 135–147, 1999.## 
[30]  A. Al-Haj, A. A. Mohammad, and L. Bata, “DWT based  audio watermarking, Int. Arab J. Inf. Technol.,vol. 8(3), pp. 326-333, 2011.## 
[31]  M. Mosleh, et al., “Presenting a systematic method for LU decomposition of a matrix with linear systolic arrays,” In book presenting a systematic method for LU decomposition of a matrix with linear systolic arrays, Series Presenting a systematic method for LU decomposition of a matrix with linear systolic arrays, IEEE, pp.123–127, 2008.## 
[32]  A. Zplane Lerch, “Development, Eaqual Evaluate Audio Quality,” version: 0.1. 3alpha, 2002.## 
[33]  A. Kaur and M. K. Dutta, “An optimized high payload audio watermarking algorithm based on LU-factorization,” Multimedia Systems, vol. 24(3), pp. 341-353, 2018.## 
[34]  H. Latifpour, M. Mosleh, and M. Kheyrandish, “An intelligent audio watermarking based on KNN learning algorithm,” International Journal of Speech Technology, vol. 18(4), pp. 697-706, 2015.## 
[35]  H. Karajeh, et al., “A robust digital audio watermarking scheme based on DWT and Schur decomposition. Multimedia Tools and Applications,” vol. 78(13), pp. 18395-18418, 2019.## 
Electronic and Cyber Defense
Volume 9, Issue 1 - Serial Number 33
Serial No. 33, Spring Quarterly
April 2021
Pages 101-113

Files

History

  • Receive Date: 15 April 2020
  • Revise Date: 15 June 2020
  • Accept Date: 05 August 2020
  • Publish Date: 21 April 2021

Share

How to cite

Statistics