Audio watermarking based on synergy between Lucas regular sequence and Fast Fourier Transform

Pourhashemi, Seyed Mostafa; Mosleh, Mohammad; Erfani, Yousof

doi:10.1007/s11042-019-7595-3

Cited by 12 publications

(11 citation statements)

References 38 publications

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“…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.…”

Section: Related Researchmentioning

confidence: 99%

“…However, the data payload of this method is not reported there. In [6], a watermarking scheme was proposed based on Lucas regular sequence (LRS) and FFT. However, this scheme shows less robustness against some of the common attacks.…”

Section: Related Researchmentioning

confidence: 99%

“…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.…”

Section: Related Researchmentioning

confidence: 99%

“…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…”

Section: Referencementioning

confidence: 99%

“…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.…”

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confidence: 99%

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

2020

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Digital watermarking has been widely utilized for ownership protection of multimedia contents. This paper introduces a blind symmetric audio watermarking algorithm based on parametric Slant-Hadamard transform (PSHT) and Hessenberg decomposition (HD). In our proposed algorithm, at first watermark image is preprocessed to enhance the security. Then, host signal is divided into non-overlapping frames and the samples of each frame are reshaped into a square matrix. Next, PSHT is performed on each square matrix individually and a part of this transformed matrix of size m×m is selected and HD is applied to it. Euclidean normalization is calculated from the 1st column of the Hessenberg matrix, which is further used for embedding and extracting the watermark. Simulation results ensure the imperceptibility of the proposed method for watermarked audios. Moreover, it is demonstrated that the proposed algorithm is highly robust against numerous attacks. Furthermore, comparative analysis substantiates its superiority among other state-of-the-art methods.

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