scholarly journals Digital Audio and Speech Watermarking Based on the Multiple Discrete Wavelets Transform and Singular Value Decomposition

2012 ◽  
Author(s):  
Mohammad Ali Nematollahi ◽  
S.A.R Al-Haddad ◽  
Shyamala Doraisamy ◽  
M. Iqbal Bin Saripan
Keyword(s):  
Singular Value Decomposition ◽  
Singular Value ◽  
Digital Audio ◽  
Speech Watermarking ◽  
Wavelets Transform ◽  
Discrete Wavelets ◽  
Value Decomposition

Digital Speech Watermarking Based on Linear Predictive Analysis and Singular Value Decomposition

2017 ◽  
Vol 87 (3) ◽  
pp. 433-446 ◽  
Author(s):  
Mohammad Ali Nematollahi ◽  
Chalee Vorakulpipat ◽  
Hamurabi Gamboa-Rosales ◽  
Francisco J. Martinez-Ruiz ◽  
Jose I. De la Rosa-Vargas
Keyword(s):  
Singular Value Decomposition ◽  
Singular Value ◽  
Predictive Analysis ◽  
Speech Watermarking ◽  
Digital Speech Watermarking ◽  
Value Decomposition ◽  
Linear Predictive Analysis

scholarly journals Pengaruh Kapasitas Dimensi Citra Watermark terhadap Audio Watermarking dengan Perpaduan Metode DWT (Discrete Wavelet Transform) dan SVD ( Singular Value Decomposition)

2019 ◽  
Vol 6 (2) ◽  
pp. 141
Author(s):  
Togu Novriansyah Turnip ◽  
Jenny Doloksaribu ◽  
Vedtra Purba ◽  
Immanuel Saragih
Keyword(s):  
Wavelet Transform ◽  
Singular Value Decomposition ◽  
Discrete Wavelet Transform ◽  
Audio Signal ◽  
Singular Value ◽  
Audio Watermarking ◽  
Discrete Wavelet ◽  
Digital Audio ◽  
Copyright Information ◽  
Value Decomposition

<p class="Abstrak">Digital audio <em>watermarking</em> dibutuhkan untuk memberi perlindungan dari pembajakan musik secara ilegal dan pemberian hak cipta/kepemilikan. Penelitian ini menjelaskan perpaduan metode audio <em>watermarking</em> dimana informasi berupa hak cipta disisipkan ke dalam sinyal audio. Perpaduan dari metode DWT (<em>Discrete Wavelet Transfrom</em>) dan SVD (<em>Singular Value Decomposition</em>) digunakan untuk menyisipkan dan mengekstrak <em>watermark</em> dari sinyal audio. Informasi atau watermark tersebut dapat berupa gambar hitam putih (<em>biner</em>) atau huruf-huruf karakter ASCII. Pada penelitian ini sebuah gambar dijadikan sebagai <em>watermark</em> dengan berbagai variasi ukuran piksel seperti 10×10, 30×30, 40×40 dan 50×50 piksel. Hasil dari penyisipan <em>watermark</em> yang berukuran 30×30 piksel menghasilkan <em>imperceptibility</em> 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 (<em>robustness</em>) terhadap beberapa serangan seperti <em>amplify</em>, <em>resampling</em> dan <em>invert</em>.</p><p class="Abstrak"><strong><em>Abstract</em></strong></p><p class="Judul2"><em>Digital audio watermarking is needed as a protection against online music piracy and </em><em>copyright issues</em><em>. This paper describes an audio watermarking</em><em> combination</em><em> method where </em><em>the </em><em>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 e</em><em>x</em><em>tract the watermark from the audio signal. The copyright information or watermark could be a binary logo or some unique binary pattern</em><em>s</em><em>. In this paper, a watermarked image </em><em>is </em><em>divided into four different capacities of dimension such as 10×10, 30×30</em><em>, </em><em>40×40 and 50×50 pi</em><em>x</em><em>el</em><em>s</em><em>.</em><em> </em><em>The result</em><em>s</em><em> of the watermarked image </em><em>are</em><em> imperceptibly added into the audio signal</em><em> and image with</em><em> 30×30 pixel </em><em>dimension </em><em>ha</em><em>s</em><em> the best mean result ranged from 43 to 50 dB</em><em>.</em><em> The experiment result also show</em><em>s</em><em> that the combination of DWT and SVD is robust against different attacks such as amplify, resampling and invert.</em></p><p class="Judul2"> </p>

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