By Pranab Kumar Dhar, Tetsuya Shimamura
This booklet introduces audio watermarking equipment for copyright defense, which has drawn huge recognition for securing electronic facts from unauthorized copying. The publication is split into components. First, an audio watermarking procedure in discrete wavelet rework (DWT) and discrete cosine rework (DCT) domain names utilizing singular worth decomposition (SVD) and quantization is brought. this technique is powerful opposed to a variety of assaults and gives solid imperceptible watermarked sounds. Then, an audio watermarking strategy in quickly Fourier rework (FFT) area utilizing SVD and Cartesian-polar transformation (CPT) is gifted. this system has excessive imperceptibility and excessive info payload and it offers solid robustness opposed to numerous assaults. those options permit media proprietors to guard copyright and to teach authenticity and possession in their fabric in numerous purposes.
· good points new equipment of audio watermarking for copyright safeguard and possession protection
· Outlines concepts that supply stronger functionality when it comes to imperceptibility, robustness, and knowledge payload
· contains functions similar to info authentication, information indexing, broadcast tracking, fingerprinting, etc.
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Extra info for Advances in Audio Watermarking Based on Singular Value Decomposition
9) where P is the BER probability of the extracted watermark. The approximate value of P can be obtained from the BER under different attacks. From the simulation results, we observed that all the BER values are less than 0:04. Thus P is taken as 0:96. By substituting the values of k and P , Eq. 9 gives PF NE D 1:3566 10 80 . 0; 100, which indicates that the FNE probability approaches 0 when k is larger than 20. 02 0 0 20 40 60 80 100 k Fig. 4 Data Payload The data payload (also known as the capacity) of a watermarking method is defined as the number of bits that can be embedded into the original audio signal within a unit of time and is measured in bits per second (bps).
The main idea of patchwork based method is to select two patches (data sets) randomly from the original signal and the mean values of these two patches are modified by a constant value, which defines the watermark strength. Consider, two randomly selected patches A and B with size N . 1) where ai0 , bi0 are the modified sample values and ai , bi are the original sample values of the patches A and B, respectively, i D 1; 2; : : : ; N , and d is a small constant. 2) The expected value of sample mean difference of modified sample values EŒa0 b 0 is calculated to decide whether the patch contains watermark information or not.
14) ! 2; 2/ of each matrix Si are also preserved to utilize in detection process. 16) Each matrix Ri0 is then reshaped to create the l modified FFT coefficients of each frame Fi by performing the inverse operation of step 3. Step 12: After substituting the l modified FFT coefficients for first l low frequency FFT coefficients of each frame Fi , an inverse FFT is applied to the FFT coefficients of each frame Fi to obtain the watermarked audio frame Fi0 . Step 13: Finally, all watermarked frames are concatenated to calculate the watermarked audio signal X 0 .
Advances in Audio Watermarking Based on Singular Value Decomposition by Pranab Kumar Dhar, Tetsuya Shimamura