scholarly journals Intelligent High Payload Audio Watermarking Algorithm Using Colour Image in DWT-SVD Domain

2021 ◽  
Vol 2128 (1) ◽  
pp. 012019
Author(s):  
A R Elshazly ◽  
Mohamed E. Nasr ◽  
M M Fouad ◽  
Fathi E. Abdel-Samie
Keyword(s):  
Chaotic Map ◽  
Audio Signal ◽  
Audio Watermarking ◽  
Discrete Wavelet ◽  
Watermark Image ◽  
Colour Image ◽  
Blind Extraction ◽  
Approximation Coefficients ◽  
Value Decomposition ◽  
High Payload

Abstract Copyright protection and ownership verification of digital audio tracks have become increasingly important to be enabled by digital watermarking techniques. A novel high payload intelligent audio watermarking scheme with RGB color watermark image is proposed in this paper. The color watermark image is encrypted using Arnold chaotic map and passed through an adaptive scaling filter to scale the image to match the required payload. The encoding process is performed on the scaled encrypted version of the watermark image. A portion of the audio signal is used to embed a synchronization code and the other one is decomposed into short frames. These frames are processed with a two-level discrete wavelet transform (DWT), followed by a singular value decomposition (SVD) process on the approximation coefficients. The encoded watermark is inserted into the diagonal matrix using quantization index modulation (QIM). The inverse process of SVD and DWT is applied to obtain the marked audio signal. Blind extraction of the hidden information from the marked audio signal is performed in the reverse order of the embedding process. Experiments show that security, high payload, transparency and imperceptibility of the algorithm are satisfied. The robustness against several kinds of audio signal processing attacks is shown. Performance evaluation tests with SNR, BER, and FSIM are conducted.

scholarly journals A robust watermarking hybrid algorithm for color image

2021 ◽  
Vol 336 ◽  
pp. 07012
Author(s):  
Mengli Song ◽  
Huijun Wang ◽  
Jianbin Wu ◽  
Xinrong Yan ◽  
Linfeng Yuan ◽  
...  
Keyword(s):  
Copyright Protection ◽  
Hybrid Algorithm ◽  
Color Image ◽  
Image Transmission ◽  
Discrete Wavelet ◽  
Watermark Image ◽  
Robust Watermarking ◽  
Watermark Embedding ◽  
Blind Extraction ◽  
Value Decomposition

In order to improve the anti-attack performance of the watermark to meet the requirements of copyright protection and content forensics. This paper proposes a digital watermarking hybrid algorithm based on color images. The specific process is to adopt the idea of multi-algorithm layered embedding, choose the algorithm based on discrete cosine transform (DCT) algorithm, discrete wavelet transform_singular value decomposition (DWT_SVD) algorithm, and hologram algorithm, these three algorithms with robust complementary functions, then embed the same watermark image into the color image R, G and B layers to complete the watermark embedding. Compared with the single-algorithm embedded watermark, the hybrid algorithm can achieve blind extraction, at the same time, the algorithm has better robustness and can resist more types and higher intensity attacks. In the process of digital image transmission, the integrity of the watermark information of the carried picture can be guaranteed to achieve copyright protection, content forensics and other purposes.

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>

AUDIO WATERMARKING WITH ANGLE QUANTIZATION BASED ON DISCRETE WAVELET TRANSFORM AND SINGULAR VALUE DECOMPOSITION

2018 ◽  
Vol 6 (2) ◽  
pp. 41-52
Author(s):  
Divya Chadar ◽  
Shailja Shukla
Keyword(s):  
Wavelet Transform ◽  
Singular Value Decomposition ◽  
Discrete Wavelet Transform ◽  
Auditory System ◽  
Audio Signal ◽  
Singular Value ◽  
New Method ◽  
Discrete Wavelet ◽  
Audio Watermark ◽  
Value Decomposition

An audio watermark is a unique electronic identifier embedded in an audio signal, typically used to identify ownership of copyright. Proposed work is a new method of audio watermark hiding inside another bigger cover standard audio cover. The method includes ‘harr’ wavelet based Discrete Wavelet Transform decomposition of frequencies hence the audio samples of watermark gets hidden only those parts of cover audio where human ears are less sensible according to Human Auditory System. Proposed method also includes the Singular Value Decomposition, which is required for making our method robust against the various communication of processing attacks like compression, filtering, fading or noise addition. Proposed work is also using the concept of angular modulation which initially modifies the audio watermark in to provide extra security and also extra robustness in communication. The design is been develop on MATLAB 2013b version and verification of design o the same. 

A Method about Embedding Watermark in PDF Document

2014 ◽  
Vol 530-531 ◽  
pp. 841-845
Author(s):  
Shun He ◽  
Yu Hui Li ◽  
Bo Li ◽  
Yu Lian
Keyword(s):  
Wavelet Transform ◽  
Singular Value Decomposition ◽  
Document Image ◽  
Singular Value ◽  
Discrete Wavelet ◽  
Watermark Image ◽  
Original Image ◽  
Copyright Information ◽  
Value Decomposition ◽  
Image Format

A method about embedding watermark in PDF document is proposed in this paper. First, PDF document is converted into a image format. Watermark image is converted into a scrambling image by Arnold transformation.And then the watermark is embedded into the PDF document image by discrete wavelet transform for PDF document image and matrix singular value decomposition for watermark image. Not only can watermark be extracted without the original image, but also increase the safety by this means. Experiment express, on the condition that the same size of the watermark image,the method made more copyright information as watermark be embedded into PDF document and the amount of the watermarked PDF document data be affected less with the increase of copyright information.

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

Symmetry ◽  
2018 ◽  
Vol 10 (7) ◽  
pp. 284 ◽  
Author(s):  
Qiuling Wu ◽  
Meng Wu
Keyword(s):  
Audio Signal ◽  
Audio Watermarking ◽  
Discrete Wavelet ◽  
Chaotic Encryption ◽  
Average Amplitude ◽  
Blind Audio Watermarking ◽  
Hybrid Domain ◽  
Frequency Components ◽  
Special Embedding ◽  
Audio Media

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.

Audio Watermarking Based on Wavelet Transform

2012 ◽  
Vol 229-231 ◽  
pp. 2784-2788 ◽  
Author(s):  
Mahmoud A. Osman ◽  
Nasser H. Ali
Keyword(s):  
Wavelet Transform ◽  
High Frequency ◽  
Low Frequency ◽  
Audio Signal ◽  
Frequency Component ◽  
Binary Image ◽  
Audio Watermarking ◽  
High Frequency Component ◽  
Discrete Wavelet ◽  
Copyright Information

The process of hiding the information like text, binary image, audio etc. into another signal source like image, audio etc. is called watermarking. The approach involved in watermarking the binary image signal in the wavelet domain of the audio signal was implemented using MATLAB. In this paper, we propose a Discrete Wavelet Transform low frequency to high frequency. Besides, the high frequency spectrum is less sensitive to human ear. That is the reason why the high frequency component is usually discarded in the compression process. Therefore, information to be hidden can be embedded into the low frequency component to against the compression attack. The characteristic of this scheme is that the user can not only use the DAW to embed the text file in to the audio but also binary image. In this paper we embeds copyright information into audio files as a proof of their ownership, we propose an effective, robust, and an inaudible audio watermarking algorithm. The effectiveness of the algorithm has been brought by virtue of applying the discrete wavelets transform (DWT) . Experimental results will be presented in this paper to demonstrate the effectiveness of the proposed algorithm.

Research on Digital Watermarking Algorithm Based on Discrete Wavelet Transform and Singular Value Decomposition

2015 ◽  
Vol 713-715 ◽  
pp. 1843-1846
Author(s):  
Yan Yu Wang
Keyword(s):  
Wavelet Transform ◽  
Discrete Wavelet Transform ◽  
Digital Watermarking ◽  
Singular Values ◽  
Discrete Wavelet ◽  
Watermark Image ◽  
Original Image ◽  
Host Image ◽  
Important Means ◽  
Value Decomposition

Digital watermarking technology has become an important means of integrity and respect for people's authenticity, as well as users of copyright and intellectual property security and other interests such as the protection of digital works. In this paper, we proposed a watermarking algorithm based on discrete wavelet transform (DWT) of image and singular valued composition (SVD). The original image is decomposed with DWT,the watermarking image is decomposed with SVD after chaotic scrambling,and then the singular values of watermarking are embedded into some coefficients of decomposed original image. In this algorithm, after decomposing the original host image into four bands, we apply the SVD to watermark image,and modify DWT coefficients of the host image with the singular values of the watermark image. The outstanding features of the proposed algorithm are that it provides larger watermarking capacity and is more robust than others.

scholarly journals Fusion Based Watermarking Scheme with Multi Level DWT & SVD

2018 ◽  
Vol 7 (3.6) ◽  
pp. 270
Author(s):  
Ch Hima Bindu ◽  
Maruturi Haribabu ◽  
K Veera Swamy
Keyword(s):  
Singular Value Decomposition ◽  
Mean Square Error ◽  
Singular Value ◽  
Cover Image ◽  
Discrete Wavelet ◽  
Mean Square ◽  
Watermark Image ◽  
Multi Level ◽  
Value Decomposition ◽  
Watermarking Scheme

This paper proposes “Fusion based watermarking with multi level DWT & singular value decomposition” has been implemented. In watermarking scheme, maintaining security and robustness is major hurdle. To address this issue we proposed a novel non blind embedding scheme with Discrete Wavelet transform (DWT) and Singular Value Decomposition (SVD) techniques. This paper details the design of the proposed watermarking scheme and analyses its robustness in the presence of various possible security attacks that involves in degrading the quality of watermark. In the beginning, the cover image color component (especially Red Component) is decomposed into LL, LH, HL, HH with 2 level DWT: these LH & HL coefficients are further divided into 8*8 blocks and each block is compared to build a fused coefficient. Apply SVD on fused coefficient of cover image and watermark image to embed the singular values with sigmod scaling factor. Finally the watermarked image is generated, after applying inverse SVD & 2 level DWT. At receiver side the inverse process has been implemented to extract watermark image. The efficiency and performance of the proposed method is verified with   Peak Signal to Noise Ratio (PSNR), Root mean square error (RMSE) and Mean Square error (MSE) and compared with recent works of santhi [12] and harsha [13].  

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