Adjustable audio watermarking algorithm based on DWPT and psychoacoustic modeling

Hemis, Mustapha; Boudraa, Bachir; Megías, David; Merazi-Meksen, Thouraya

doi:10.1007/s11042-017-4813-8

Cited by 9 publications

(24 citation statements)

References 45 publications

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“…In the extraction stage, the watermark was detected by a linear correlation method. Based on embedding synchronization code to resist synchronization attacks, Hemis et al [8] applied the psychoacoustic model [9] to select the signals under the global masking threshold as the embedding position, and then distortioncompensated dither modulation (DC-DM) quantization was used to embed the watermark into the coefficients of the discrete wavelet packet transform (DWPT).…”

Section: A Prior Related Approachesmentioning

confidence: 99%

“…Multimedia watermarking can be implemented with software-based watermarking or hardware-based watermarking. The implementation of software-based watermarking is flexible, [1]- [8] belongs to this watermark. On the other hand, hardware-based watermarking has high embedding efficiency.…”

Section: A Prior Related Approachesmentioning

confidence: 99%

“…1) The approaches in [1]- [8] segmented the audio signal by a fixed length, which would weaken the robustness to synchronization attacks. Segmentation is the key step in watermarking.…”

Section: B Motivation Of the Papermentioning

confidence: 99%

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

et al. 2019

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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.

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Section: A Prior Related Approachesmentioning

confidence: 99%

Section: A Prior Related Approachesmentioning

confidence: 99%

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

et al. 2019

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“…With the rapid development of the Internet and multimedia technologies, it is convenient to transmit digital information all over the world quickly. However, the information security problem has become a global issue to be solved [1][2][3]. A digital watermarking algorithm is an effective method to protect media content in the fields of copyright protection, fingerprint identification, broadcast monitoring, medical security, data authentication and so on.…”

Section: Introductionmentioning

confidence: 99%

“…Over the past decades, many audio watermarking algorithms have appeared in different domains, such as the time and transform domains. In general, the time domain watermarking algorithm is easy to implement, but less robust in combating various digital signal processing attacks [2,4], such as the algorithms in literature [10,11]. Compared with the time-domain algorithms, the algorithms in the transform-domain, such as the discrete Fourier transform (DFT) [12][13][14], discrete cosine transform (DCT) [15,16], discrete wavelet transform (DWT) [17][18][19][20][21] and singular value decomposition (SVD) [22,23] and so on, are more robust because they explore human auditory properties and the features of audio signal.…”

Section: Introductionmentioning

confidence: 99%

Adaptive and Blind Audio Watermarking Algorithm Based on Chaotic Encryption in Hybrid Domain

2018

Symmetry

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An adaptive and blind audio watermarking algorithm is proposed based on chaotic encryption in discrete cosine transform (DCT) and discrete wavelet transform (DWT) hybrid domain. Since human ears are not sensitive to small changes in the high-frequency components of the audio media, the encrypted watermark can be embedded into the audio signal according to the special embedding rules. The embedding depth of each audio segment is controlled by the overall average amplitude to effectively improve the robustness and imperceptibility. The watermark is encrypted by a chaotic sequence to improve the security of watermark, so only users who hold the correct key can accurately extract the watermark without the original audio signal. Experimental results show that the proposed algorithm has larger capacity, higher imperceptibility, better security, and stronger robustness when combating against signal-processing attacks than the involved audio watermarking algorithms in recent years.

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A robust watermarking method for MPEG-4 SLS audio

Luo

Peng

2020

Multimed Tools Appl

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Adjustable audio watermarking algorithm based on DWPT and psychoacoustic modeling

Cited by 9 publications

References 45 publications

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

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

Adaptive and Blind Audio Watermarking Algorithm Based on Chaotic Encryption in Hybrid Domain

A robust watermarking method for MPEG-4 SLS audio

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