Dual-Domain Audio Watermarking Algorithm Based on Flexible Segmentation and Adaptive Embedding

Abstract

This paper proposes a novel dual-domain audio watermarking approach based on flexible segmentation and adaptive embedding aimed to improve robustness and imperceptibility. Compared with conventional watermarking strategies, the proposed approach has two advantages. First, a novel audio beat detection approach is designed to flexibly segment the audio, which provides stronger robustness to synchronization attacks. The audio is decomposed by the discrete wavelet packet transform. Then, the covariance relationships of the decomposition coefficients at different time instants are calculated to determine the locations of the beats and to establish a flexible segmentation model. Second, a dual-domain embedding approach is proposed to realize better robustness to compression attacks while maintaining imperceptibility. In each segment, the psychoacoustic model is used to calculate the audio masking threshold, which divides the signals into the masking signal domain and masked signal domain. The signals in the masking signal domain are robust to compression attacks, and the signals in the masked signal domain have better imperceptibility. To combine these advantages, we embed the watermark into the two domains simultaneously by using the distortion-compensated dither modulation quantization approach. To reduce the impact of the watermark on the original audio, the frequency band with the lowest mask-to-noise ratio is selected as the embedding position for each domain. Moreover, the adaptive quantization steps are calculated to control the embedding strength according to the masking effect. The adaptive embedding will improve the robustness to compression attacks without significantly affecting the original audio quality. The effectiveness of our approach is verified through simulation experiments. INDEX TERMS Audio beats, dual-domain, DWPT, DC-DM, psychoacoustic model.

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

“…Hwang et al [11] introduced a watermarking method based on quantization index modulation (QIM) and SVD, but the imperceptibility and robustness of this scheme is a little low. In [12], a watermarking method is proposed based on flexible segmentation (FS) and adaptive embedding (AE), but it provides low SNR and low robustness against some common attacks. Hu et al [13] suggested a method in dual domain using flexible segmentation and adaptive embedding where binary watermark bits are inserted into discrete wavelet packet transform coefficients.…”

“…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.…”

“…It is observed that all ODGs of our proposed algorithm range from −0.39 to −0.46, indicating that the original and watermarked audios are perceptual similar. Table 3 shows a comparative analysis between the proposed and several recent methods [4,12] in terms of SNR and MOS. From this comparison, it was observed that our proposed method shows better result in terms of SNR and MOS.…”

“…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.…”