An Effective Watermarking Method Based on Energy Averaging in Audio Signals

Abstract

Methods based on discrete cosine transform (DCT) have been proposed for digital watermarking of audio signals; however, the watermark is often vulnerable to data compression and signal processing. This paper presents an effective audio watermarking method by energy averaging of DCT coefficients such that an audio signal with watermark is robust to data processing. The method is to divide an audio signal into segments by three parameters defining the segment length, the segment sequence of watermark location, and the frequency range of DCT coefficients for watermark location. An error correcting code is also integrated to improve audio signal quality after watermarking. Experimental results show that the method is robust to data compression and many other kinds of signal processing. No original signal is required for decoding the watermark. Comparison of watermarking performance with a recent work validates that the watermarking method has better audio quality and higher robustness.

Blind Audio Watermarking Based on Parametric Slant-Hadamard Transform and Hessenberg Decomposition

“…On the other hand, the transform domain technique is applied to coefficients obtained as the result of transformation of either a whole audio or the frame of the audio. Some well-known and conventional transform domain techniques are discrete wavelet transform (DWT) [4], discrete cosine transform (DCT) [5], and fast fourier transform (FFT) [6]. Pandey et al [3] presented a method that uses the pseudo-random gray sequence property.…”

“…Kaur et al [4] suggested a method based on a mathematical model by using features such as energy, short time energy, and zero cross means, but robustness against some attacks is quite low. Tsai et al [5] proposed a watermarking method based on energy averaging. However, the data payload of this method is not reported there.…”

“…Simulation results demonstrated that our proposed method is highly robust against numerous attacks. The BER of the proposed method varies from 0 to 6.54, whereas the BER of the recent methods [4][5][6][7][8][9][10][11][12] vary from 0 to 17.76. The PSNR of the proposed method varies from 43.81 to 47.75, whereas PSNR of the recent methods vary from 19.39 to 44.81.…”

“…Method SNR MOS [4] Energy averaging 41.47 - [5] Localized and self-adaptive algorithm 31.40 3.7 [6] LRS-FFT 44.81 - [7] DCT-SVD-ELO 33.47 4.88 [8] SSA-PM 25.61 - [9] Multifunctional algorithm 23.33 - [10] DCT-SVD-LPT 37.20 4.85 [11] SVD-QIM 19.39 - [12] FS-AE 33.6 -Proposed PSHT-HD 46.56 4.95…”

“…From these figures, we observed that watermark is extracted without any errors in most of the cases, which proves the high robustness of the proposed method. Table 6 illustrates a comparative analysis between the proposed and some recent methods [4][5][6][7][8][9][10][11][12] in terms of noise addition, resampling, re-quantization, and MP3 compression. From this table, we observed that our proposed method shows less BER than the other recent methods for noise addition.…”