An audio watermark is a unique electronic identifier embedded in an audio signal, typically used to identify ownership of copyright. It is similar to a watermark on a photograph. Download the best ppt on Audio Watermarking.

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2. Introduction
 Digital Data can be shared by multiple users, distributed over network, and
managed for long period time without any damage.
 In contrast to these, the copyright protection problem arises, since unauthorized
copying and distribution of digital data are simplified, too.
 As a result, a technique called digital watermarking is introduced to protect the
ownership of these contents.

3. AUDIO WATERMARKING
Digital Audio Watermarking is a technology to hide information in an audio file
without the information being audible to the listener, and without affecting in any
way the audio quality of the original file.
What we can define ?
AIMS AT
 Copy control of digital music
 Ownership identification
 Enforcement of usage policy
 Fingerprinting

4. AUDIO WATERMARKING CHARACTERISTICS
 Transparency: watermark is not detectable
 Robustness: survives digital processing (e.g., compression) and
malicious analytical attacks.
 Efficiency: low cost implementation using minimal resources
 Independence: of both the type and format of multimedia data (e.g.,
music, speech, video, sample rates, coding scheme, ...)

5. CLASSIFICATION OF AUDIO WATERMARKING
Temporal watermarking
• Temporal watermarking hides watermarks directly into digital audio signals in
the time domain.
Spectral water-marking
• The spectral audio watermarking applies certain frequency transform, such as
FFT, DCT, and DWT, etc, to the data block of the audio signal, and hides the
watermark information Into the transformed data block.

6. AUDIO WATERMARKING SCHEMES
 DC level shifting
 QMF bank band division
 Frequency masking
 Spread spectrum

7. DC LEVEL SHIFTING
 Here watermark is embedded by shifting the DC level of the audio signal.
 An input signal is divided into frames of fixed length.
 DC level of each frame =Mean of a frame-value in the frame
 After that a binary watermark sequence generated randomly is introduced to the shifted signal.
 This is achieved by introducing a DC offset level to each frame in the signal according to the
watermark bits.
 If the watermark bit is 0, the signal is shifted downward.
 If the watermark bit is 1, the signal is shifted upward.
Cont..

8. DC LEVEL SHIFTING
level0=-DCBiasMultiplier x FramePower
level1=+DCBiasMultiplier x FramePower
where
level0 ->DC level introduced when a watermark bit is 0
level1 -> the DC level introduced when a watermark bit is 1.
 To extract a watermark, a watermarked signal is first divided into frames.
 Then, the mean of each frame is calculated. If the mean of a frame is positive,
the corresponding watermark bit is 1. Else, the watermark bit is 0.
 The original signal and watermark is not needed in the extraction process.
Therefore, DC level shifting is a blind watermarking scheme.

9. Band Division Based on Quadrature Mirror Filter (QMF) Bank
Cont..

10. Cont..

11.  Watermarked signal is filtered by the analysis filter bank and the low frequency
watermarked band is extracted out.
 The modified MDCT coefficients are calculated out and watermark can be
determined by rounding the coefficients and observe whether coefficients are
even or odd.
Watermark is 1 when coefficients are odd.
Watermark is 0 when coefficients are even.
This technique has a
 High signal to noise ratio
 The rate of detection or bit error rate is very high
WATERMARKED SIGNAL EXTRACTION USING QMF

12. FREQUENCY MASKING
 Watermarking involves hiding a faint but audible sound under another louder
sound (original sound).
 So the faint sound becomes inaudible and it acts as a watermark for the
original sound.
 Watermark is generated firstly by creating a pseudo-noise sequence (PN
sequence) from a shift register.
 The shift register consists of m flip-flops with a maximum period of (2m) – 1.
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13.  PN sequence is filtered along with the filter that approximates the frequency
characteristics of the human auditory system (HAS).
 Consequently, it is put through to the time domain for temporal masking.
 The frequency masking algorithm is robust to coding, multiple watermarking, and
resampling.
 Different watermark can be embedded by this algorithm into the same signal and is
easy to detect by the owner.
 The detection scheme for this algorithm needs the original input signal, which is not
flexible
 From the extraction scheme, frequency masking is a private watermarking.

14. SPREAD SPECTRUM
Where
wi is element of watermark
y is the watermarked signal
A correlation detector is carried out to detect the presence of the watermark and is
described by Eqn
where N is vector cardinality Cont..

15. SPREAD SPECTRUM
While x can be modelled as Gaussian random vector, the normalised correlation test
is described as Eqn
 
1
0, /
^ 2
x
C
Q p N N
N
  
 
If p = 1, watermark is present
If p=0, watermark is not present

16. ANALYSIS OF VARIOUS TECHNIQUES
• DC level shifting algorithm
 The robustness level for the DC level shifting is poor
 The watermark can be easily removed by altering the DC levels of the signal and the watermark is
destroyed.
• Frequency Masking
 This method is not robust to filtering because watermark is embedded to all frequency bands.
 Attack by high pass filter MPEG can erase the watermark.
Cont..

17. • Spread Spectrum & Band Division Based On QMF
 Both the band division method and the spread spectrum method are capable of defending against the
MP3 compression, but the spread spectrum has a better detection rate than the band division method.
 The implementation steps for spread spectrum are more complicated. This makes it hard to hack and
breakdown the algorithm.
• Band Division Based On QMF
 Band division technology performs extraction scheme with no original signal require attacks are still not
upgraded to hack down this audio watermarking technology.

18. CONCLUSION
 Watermark can be embedded in an audio signal without being
recognized by hearing and the perceptibility requirement is fulfilled .
 Extraction can be done without the presence of the original signal and
the watermark itself, so can be classified as blind or public
watermarking.

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