By Pranab Kumar Dhar, Tetsuya Shimamura
This publication introduces audio watermarking equipment for copyright defense, which has drawn broad awareness for securing electronic info from unauthorized copying. The ebook is split into components. First, an audio watermarking approach in discrete wavelet remodel (DWT) and discrete cosine rework (DCT) domain names utilizing singular worth decomposition (SVD) and quantization is brought. this system is strong opposed to quite a few assaults and offers reliable imperceptible watermarked sounds. Then, an audio watermarking process in quickly Fourier remodel (FFT) area utilizing SVD and Cartesian-polar transformation (CPT) is gifted. this system has excessive imperceptibility and excessive information payload and it offers stable robustness opposed to a variety of assaults. those concepts let media proprietors to guard copyright and to teach authenticity and possession in their fabric in numerous functions.
· beneficial properties new equipment of audio watermarking for copyright defense and possession protection
· Outlines innovations that offer more suitable functionality when it comes to imperceptibility, robustness, and information payload
· contains purposes similar to info authentication, facts indexing, broadcast tracking, fingerprinting, etc.
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Additional info for Advances in Audio Watermarking Based on Singular Value Decomposition
These parameters have been selected in order to achieve a good trade-off among the conflicting requirements of imperceptibility, robustness, and data payload. 5, respectively show the magnitude spectrum of a selected frame for the original and watermarked audio signal ‘Folk’ using the proposed method. 1 Imperceptibility Test Generally, there are two approaches to perform perceptual quality assessment: (i) subjective evaluation test and (ii) objective evaluation test. 1 Subjective Evaluation Test SDG has been used extensively for evaluating the quality of watermarked audio signal.
In addition, the ABX method, which is another subjective quality assessment technique, was employed to investigate the sound quality of the watermarked audio signal. The participants were ten male and female persons with normal hearing ability. In this test, the original audio signal ‘A’ and the watermarked audio signal ‘B’ were presented to each participant. A third audio signal ‘X’ is presented in random order, which can be either ‘A’ or ‘B’. The participants were asked to identify which of ‘A’ or ‘B’ was the same as ‘X’.
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). 10) Usually, the data payload for any watermarking method should be more than 20 bps .
Advances in Audio Watermarking Based on Singular Value Decomposition by Pranab Kumar Dhar, Tetsuya Shimamura