A NOVEL METHOD FOR REAL-TIME AUDIO WATERMARKING USING
WAVELET TRANSFORM
Mahmood Movassagh, Ali Asghar Beheshti Shirazi
Department of Electrical Engineering, Iran University of Science and Technology (IUST)
mmovassagh@ee.iust.ac.ir , abeheshti@iust.ac.ir
ABSTRACT
In this paper we propose a novel method for audio
watermarking which is appropriate for real-time
applications. Here the energy proportion of two
successive low-middle frequency bands of each audio
signal frame is computed and through the use of Index
Modulation technique we embed the watermark bits
into these proportion values. Low complexity is the
most important characteristic of the proposed method
making it appropriate for real –time applications. The
method is a blind one, that is it does not need the
original signal for extracting watermark bits.
Experimental results have shown that it has a very
good robustness against common watermarking attacks
such as mp3 compression, low pass filtering,
resampling, requantizing and adding noise.
Index Terms- Audio Watermarking, Real-Time,
Wavelet Transform, Quantization Index Modulation
(QIM)
1. INTRODUCTION
With the growth of multimedia production and
broadcasting, security issues have been concerning for
multimedia producers. In recent years watermarking
has provided good means for protecting multimedia
against illegal tasks especially for copy protection,
ownership proof and modification protection.
978-1-4244-1643-1/08/$25.00 ©2008 IEEE
Although most multimedia watermarking works have
been dedicated to image watermarking so far, during
the last decade many audio watermarking methods
have been proposed [1]-[4]. For example, techniques
based on perceptual masking, spread spectrum
communications (SS), phase coding, phase
modulation, echo hiding and so on [4, 5]. Generally we
can divide watermarking techniques into two domains:
Time domain and Frequency domain. In time domain
methods watermark bits are embedded directly into the
signal time samples and in the latter, after taking one
of the usual transforms such as FFT, MDCT and WT
from the signal, watermark bits are embedded into the
resulting transform coefficients [2, 5, 6].
Among the existing transforms, wavelet transform has
some advantages in audio signal processing. Its
inherent frequency multiresolution and logarithmic
decomposition of frequency bands resembles human
perception of frequencies because it allows the
decomposition to mimic the critical band structure of
the human auditory system [7, 8]. The two other
mentioned transforms, FT and MDCT, produce equal-
spaced frequency bands which do not correspond to
human perception of the frequencies and to get
acceptable frequency resolution in low frequencies,
high frequency resolution is over-detailed. Therefore,
they are quite inefficient for audio processing
compared with the wavelet transform. Using transform
based methods provides a better perception quality and
robustness against common attacks while causing
more complexity. For real time applications
complexity is the most important task that should be
considered. In [12] an efficient audio watermarking
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