Performance Evaluation of  Digital Audio Watermarking  based on  Discrete Wavelet  Transform for  Ownership Protection

Digital audio watermarking dibutuhkan untuk memberi perlindungan dari pembajakan musik secara ilegal dan pemberian hak cipta/kepemilikan. Penelitian ini menjelaskan perpaduan metode audio watermarking dimana informasi berupa hak cipta disisipkan ke dalam sinyal audio. Perpaduan dari metode DWT (Discrete Wavelet Transfrom) dan SVD (Singular Value Decomposition) digunakan untuk menyisipkan dan mengekstrak watermark dari sinyal audio. Informasi atau watermark tersebut dapat berupa gambar hitam putih (biner) atau huruf-huruf karakter ASCII. Pada penelitian ini sebuah gambar dijadikan sebagai watermark dengan berbagai variasi ukuran piksel seperti 10×10, 30×30, 40×40 dan 50×50 piksel. Hasil dari penyisipan watermark yang berukuran 30×30 piksel menghasilkan imperceptibility yang baik dengan nilai rata-rata diantara 43 sampai dengan 50 dB. Hasil eksperimen yang telah dilakukan juga menunjukkan bahwa kombinasi dari kedua metode tahan (robustness) terhadap beberapa serangan seperti amplify, resampling dan invert.AbstractDigital audio watermarking is needed as a protection against online music piracy and copyright issues. This paper describes an audio watermarking combination method where the copyright information is imperceptibly added into the audio signal. The combination of discrete wavelet transform (DWT) and singular value decomposition (SVD) is used to embed and extract the watermark from the audio signal. The copyright information or watermark could be a binary logo or some unique binary patterns. In this paper, a watermarked image is divided into four different capacities of dimension such as 10×10, 30×30, 40×40 and 50×50 pixels. The results of the watermarked image are imperceptibly added into the audio signal and image with 30×30 pixel dimension has the best mean result ranged from 43 to 50 dB. The experiment result also shows that the combination of DWT and SVD is robust against different attacks such as amplify, resampling and invert.

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A novel audio watermarking scheme using ensemble-based watermark detector and discrete wavelet transform

Neural Computing and Applications ◽

10.1007/s00521-020-05389-2 ◽

2020 ◽

Author(s):

Seyed Mostafa Pourhashemi ◽

Mohammad Mosleh ◽

Yousof Erfani

Keyword(s):

Wavelet Transform ◽

Discrete Wavelet Transform ◽

Audio Watermarking ◽

Discrete Wavelet ◽

Watermarking Scheme

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Digital Audio Watermarking

Multimedia Security ◽

10.4018/978-1-59140-192-6.ch004 ◽

2005 ◽

pp. 126-156

Author(s):

Changsheng Xu ◽

Qi Tian

Keyword(s):

Performance Evaluation ◽

Auditory System ◽

Digital Watermarking ◽

Research Area ◽

Audio Watermarking ◽

Current Status ◽

Digital Audio ◽

Digital Audio Watermarking ◽

Big Picture ◽

Comprehensive Survey

This chapter provides a comprehensive survey and summary of the technical achievements in the research area of digital audio watermarking. In order to give a big picture of the current status of this area, this chapter covers the research aspects of performance evaluation for audio watermarking, human auditory system, digital watermarking for PCM audio, digital watermarking for wav-table synthesis audio, and digital watermarking for compressed audio. Based on the current technology used in digital audio watermarking and the demand from real-world applications, future promising directions are identified.

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Digital Audio Watermarking Scheme Based on Independent Component Analysis in DWT Domain

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.219-220.1121 ◽

2011 ◽

Vol 219-220 ◽

pp. 1121-1125 ◽

Cited By ~ 1

Author(s):

Rui Chen ◽

Yu Lin Lan ◽

Reza Asharif Mohammad

Keyword(s):

Independent Component Analysis ◽

Low Frequency ◽

Component Analysis ◽

Extraction Process ◽

Independent Component ◽

Audio Watermarking ◽

Discrete Wavelet ◽

Digital Audio ◽

Digital Audio Watermarking ◽

Watermarking Scheme

This paper proposed a digital audio watermarking scheme based on independent component analysis (ICA) in DWT domain. The embedding process make full use of the multi-resolution characteristic of discrete wavelet transform (DWT), performing 3-level DWT. Selecting the low frequency coefficient appropriately as the embed location to make sure of the balance between the transparency and robustness. Then constructing the ICA model to embed the watermarking. The extraction process is similar with ICA’s goal, it’s used in extraction makes the scheme simple for implementation. The experiment results show that the proposed scheme has good robustness against common attacks, as well as transparency.

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Audio Watermarking Based on Hybrid Low and High Wavelet Frequencies

International Journal of Informatics and Communication Technology (IJ-ICT) ◽

10.11591/ijict.v5i1.pp28-35 ◽

2016 ◽

Vol 5 (1) ◽

pp. 28

Author(s):

Aree Ali Mohammed

Keyword(s):

Time Domain ◽

Wavelet Transformation ◽

Signal To Noise Ratio ◽

Audio Watermarking ◽

Discrete Wavelet ◽

Transform Domain ◽

Digital Audio ◽

Test Results ◽

Digital Audio Watermarking ◽

Over Time

Transform-domain digital audio watermarking has a performance advantage over time-domain watermarking by virtue of the fact that frequency transforms offer better exploitation of the human auditory system (HAS). In this research paper an adaptive audio watermarking is proposed based on the low and high wavelet frequencies band (LF, HF). The embedded watermark can be of any types of signal (text, audio and image). The insertion of the watermark data is performing in a frequency domain after applying discrete wavelet transformation on the cover audio segments. The normalize correlation and the signal to noise ratio metrics are used to test the performance of the proposed method in terms of the robustness and imperceptibility. Test results show that an improvement of the robustness against some type of attacks when the watermark is adaptively embedded in a different wavelet bands.

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