Audio Watermarking Using Wavelet Transform and Genetic Algorithm for Realizing High Tolerance to MP3 Compression

Shinichi Murata, Yasunari Yoshitomi, Hiroaki Ishii
DOI: 10.4236/jis.2011.23010                

Abstract

Recently, several digital watermarking techniques have been proposed for hiding data in the frequency domain of audio signals to protect the copyrights. However, little attention has been given to the optimal position in the frequency domain for embedding watermarks. In general, there is a tradeoff between the quality of the watermarked audio and the tolerance of watermarks to signal processing methods, such as compression. In the present study, a watermarking method developed for a visual image by using a wavelet transform was applied to an audio clip. We also improved the performance of both the quality of the watermarked audio and the extraction of watermarks after compression by the MP3 technique. To accomplish this, we created a multipurpose optimization problem for deciding the positions of watermarks in the frequency domain and obtaining a near-optimum solution. The near-optimum solution is obtained by using a genetic algorithm. The experimental results show that the proposed method generates watermarked audios of good quality and high tolerance to MP3 compression. In addition, the security was improved by using the characteristic secret key to embed and extract the watermark information.

Keywords

Audio Watermarking, Genetic Algorithm, Optimization, Wavelet Transforms, Secret Key

Conflicts of Interest

The authors declare no conflicts of interest.

References

[1]	D. Kirovski and H. S. Malvar, “Spread-Spectrum Watermarking of Audio Signals,” IEEE Transactions on Signal Processing, Vol. 51, No. 4, April 2003, pp. 1020-1033.
[2]	I.-K. Yeo and H. J. Kim, “Modified Patchwork Algorithm: a Novel Audio Watermarking Scheme,” IEEE Transactions on Speech and Audio Processing, Vol. 11, No. 4, July 2003, pp. 381-386.
[3]	S. Wu, J. Huang, D. Huang and Y. Q. Shi, “Efficiently Self-Synchronized Audio Watermarking for Assured Audio Data Transmission,” IEEE Transactions on Broadcasting, Vol. 51, No. 1, March 2005, pp. 69-76.
[4]	X. Y. Wang and H. Zhao, “A Novel Synchronization Invariant Audio Watermarking Scheme Based on DWT and DCT,” IEEE Transactions on Signal Processing, Vol. 54, No. 12, December 2006, pp. 4835-4840.
[5]	S. Xiang and J. Huang, “Histogram-Based Audio WaterMarking against Time-Scale Modification and Cropping Attacks,” IEEE Transactions on Multimedia, Vol. 9, No. 7, November 2007, pp. 1357-1372.
[6]	S. Kirbiz, A. N. Lemma, M. U. Celik and S. Katzenbeisser, “Decode-Time Forensic Watermarking of AAC Bitstreams,” IEEE Transactions on Information Forensics and Security, Vol. 2, No. 4, December 2007, pp. 683-696.
[7]	D. J. Coumou and G. Sharma, “Insertion, Deletion Codes with Feature-Based Embedding: A New Paradigm for Watermark Synchronization with Applications to Speech Watermarking,” IEEE Transactions on Information Forensics and Security, Vol. 3, No. 2, June 2008, pp. 153-165.
[8]	S. Xianga, H. J. Kimb, and J. Huanga, “Audio Watermarking Robust against Time-Scale Modification and MP3 Compression,” Signal Processing, Vol. 88, No. 10, October 2008, pp. 2372-2387.
[9]	X. Y. Wang, P. P. Niu and H. Y. Yang, “A Robust, Digital-Audio Watermarking Method,” IEEE Multimedia, Vol. 16, No. 3, July 2009, pp. 60-69.
[10]	N. K. Kalantari, M. A. Akhaee, S. M. Ahadi and H. Amindavar, “Robust Multiplicative Patchwork Method for Audio Watermarking,” IEEE Transactions on Audio, Speech, and Language Processing, Vol. 17, No. 6, August 2009, pp. 1133-1141.
[11]	X. Y. Wanga, P. P. Niub and H. Y. Yangb, “A Robust Digital Audio Watermarking Based on Statistics Characteristics,” Pattern Recognition, Vol. 42, No. 11, November 2009, pp. 3057-3064.
[12]	K. Yamamoto and M. Iwakiri, “Real-Time Audio Watermarking Based on Characteristics of PCM in Digital Instrument,” Journal of Information Hiding and Multimedia Signal Processing, Vol. 1, No. 2, April 2010, pp. 59-71.
[13]	D. Goldberg, “Genetic Algorithm in Search, Optimization, and Machine Learning,” Addison-Wesley, Reading, Boston, 1989.
[14]	J. H. Holland, “Adaptation in Natural and Artificial Systems,” The University Michigan Press, Ann Arbor, 1975 and MIT Press, Cambridge, 1992.
[15]	M. Shino, Y. Choi and K. Aizawa, “Wavelet Domain Digital Watermarking Based on Threshold-Variable Decision,” Technical Report of IEICE, DSP2000-86, in Japanese, Vol. 100, No. 325, September 2000, pp. 29-34.
[16]	D. Inoue and Y. Yoshitomi, “Watermarking Using Wave- let Transform and Genetic Algorithm for Realizing High Tolerance to Image Compression,” Journal of the Institute of Image Electronics Engineers of Japan, Vol. 38, No. 2, March 2009, pp. 136-144.
[17]	M. Tanaka and Y. Yoshitomi, “Digital Audio Watermarking Method with MP3 Tolerance Using Genetic Algorithm,” Proceedings of the 2006 IEICE General Conference, Tokyo, 21 March 2006, p. 182.
[18]	M. Tanaka and Y. Yoshitomi, “Digital Audio Watermarking Method with MP3 Tolerance Using Genetic Algorithm,” Proceedings of 11th Czech-Japan Seminar on Data Analysis and Decision Making Under Uncertainty, Sendai, 15-17 September 2008, pp. 81-85.
[19]	R. Tachibana, “Capacity Analysis of Audio Watermarking Based on Logarithmic Amplitude Modification against Additive Noise,” IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences, in Japanese, Vol. J86-A, No. 11, November 2003, pp. 1197-1206.
[20]	F. Glover, “Future Paths for Integer Programming and Links to Artificial Intelligence,” Computers and Operations Research, Vol. 13, No. 5, May 1986, pp. 533-549.
[21]	M. Goto, H. Hashiguchi, T. Nishimura and R. Oka, “RWC Music Database: Database of Copyright-Cleared Musical Pieces and Instrument Sounds for Research Purposes,” Transactions of IPSJ, in Japanese, Vol. 45, No. 3, March 2004, pp. 728-738