2017 Artificial Intelligence and Robotics (IRANOPEN)
Classification of Watermarking Methods Based on
Watermarking Approaches
Mahsa Boreiry
Mohammad-Reza Keyvanpour
Department of Computer Engineering
Islamic Azad University (Qazvin Branch)
Qazvin, Iran
Mahsa.Boreiry@gmail.com
Department of Computer Engineering
Alzahra University
Tehran, Iran
keyvanpour@Alzahra.ac.ir
which may be embedded several times. Even though these are
often lost during the attack, the survival of a small watermark
can be accounted as a success. Despite of its simplicity, there
would be some problems. For example, this method is resistant
against cropping attacks but a little noise, waste or compression
can breakdown the watermark. Fig. 1 illustrated the sample of
embedding and extraction of watermark with LSB method.
Abstract— Video watermarking is the approach of adding
insensible data to video content in order to protect the owner’s
right. One of the main important issues in watermarking operation
is the watermarking robustness. The basic requirement in
watermarking is resisting in front of distortion and initial attacks,
which is commonly examined based on the data processing
standards. Many methods have been proposed in the field of video
watermarking that are resistant to certain attacks, therefore some
attacks can break the watermark. So, the correct identification of
methods and knowing the strength and weakness of each method
lead to propose appropriate solution in order to reduce the effects
of attacks with presenting secure algorithm in video
watermarking.
Keywords— Watermark, Video Watermarking, Watermarking
methods, Watermarking approaches.
I. INTRODUCTION
a) Embeding watermark
b) Watermark extraction
Fig. 1 Embedding and extraction of watermark with LSB method
Generally watermarking methods can be classified based on
embedding domain to spatial methods (pixel domain approach)
and spectral domain (transformation domain approach). In this
study the concentration is focused on spatial embedding
methods. In the following, each category will be evaluated
beside the relative examples. In this article, the watermarking
methods will be evaluated and categorized based on the
watermarking approach, while the focus is paid to investigate
some methods in each category with declaring the advantages
and disadvantages of each case[1].
B. Spread Spectrum Method
In the basic algorithm each bit of watermark aj , aj ∈[1] is
spread over a large number of chips and modulated by a binary
pseudo-noise sequence pj , pj ∈[1]. By the means of high-pass
filtering with correlation based method, the watermark can be
retrieved[2]. Diagram of this method shown in Fig. 2.
C. 2D Spread Spectrum
A 2D spread spectrum method is utilized to monitor video
data transmitted over different broadcast links for video
watermarking (just another watermarking system, JAWS)[3].
II. EMBEDING WATERMARK DOMAIN USING SPATIAL
METHODS
In the spatial domain watermarking techniques, the
watermark embedded in the host image/video by changing its
pixel values directly. The spatial domain watermarking can
hardly survive under the attacks such as lossy compression and
low-pass filter. The main goal of such methods which are based
on pixels are conceptually simple with poor computational
complexities. As a result, most of these methods are applicable
in real-time applications. In contrast, the watermark
optimization is difficult using only spatial analysis
techniques[1].
Fig. 2 Spread Spectrum diagram
D. CDMA method
In CDMA technique, one of the four least significant bitplanes will be replaced by watermark planes. The random
periodic quaternary sequence is used to select the bit-planes that
should be replaced. The 1D spread spectrum methodology is
A. LSB method
The LSB method is the most frequently used method for
embedding watermark in this field. Due to provide extraordinary
channel capacity the whole cover for a small object is used,
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employed to generate the watermark plane. This achievement is
applicable for the case in which the accumulation of signals
overlap in time and frequency domain and remain separate. The
essence of CMDA is hiding the sequence of messages with a
covering signal such as noise[4]. Fig. 3 illustrated a CDMA
transmitter and receiver.
A. DCT method
The first efficient layout of watermarking was introduced by
Knoch et al. In this method, the image was initially divided into
blocks of size 8×8, from 12 preset pairs, 2 pairs of the frequency
average coefficients are selected to transform. Then, Brush and
Pietas have developed a method to change the coefficient of
DCT and improve the restrictions of the selected block. After
dividing the images into blocks with size 8×8 the main blocks
are chosen based on the classification decisions Gaussian of
Network (Fig. 4). Then, using the DCT’s linear constraints the
middle range of frequency coefficients change. In transform
domain methods, the host signals is transformed in various
domains while the watermark embedded in chosen
coefficients[5]. The commonly used methodologies are Discrete
Cosine Transformation (DCT) and Discrete Wavelet
Transformation (DWT)[2]. Block diagram of DCT
watermarking is shown in Fig. 5.
Fig. 3 CDMA Transmitter and receiver
E. Region based energy modification (RBEM) method
In this method for embedding data the average energy or
luminance intensities will be manipulate in sub-region of each
frame. This method embeds 1 bit per 8 × 8 block to achieve high
data capacity, besides the error control method is utilized to
ensure the resistance.
A summary of investigation in video watermarking methods in
the spatial domain are illustrated in table 1.
Fig. 4 Generating frequency coefficients of image by DCT
III. EMBEDDING WATERMARK DOMAIN IN FREQUENCY
DOMAIN
In compare with watermarking with spatial domain,
watermarking in frequency domain which uses general methods
and image compression standards is stronger and more
consistent. Though, watermarking in frequency domain
attracted more attention. In this category, the watermark will be
embedded by changing the coefficient of watermark, after
applying the frequency transformation on data host. The image
frequency transformation will be categorized into Discrete
Fourier Transformation (DFT) and Discrete Cosine Transform
(DCT).
Fig. 5 Block diagram of DCT Watermarking
TABLE 1: INVESTIGATION OF VIDEO WATERMARKING METHODS IN SPATIAL DOMAIN
advantages
Disadvantages
In this method, by using energetic
signal propagation a high resistance can
be achieved.
The blind watermarking technique in
order to embed the watermark don’t use the
host signals.
Do not specifically protect the value of
DC blocks.
LSB
Fail in facing with cropping attacks,
compression, low-pass filter. Robustness
restriction, capacity limitation in data storage
and low resistance
Spread Spectrum
Resistance to geometric attacks such
as removal of inner distance, scaling,
rotation, simplicity and lack of
computational complexity and conceptual
clarity
This method change pixel value for embedding
watermarking.
Each bit of watermark aj is spread over several
chips and modulated by a binary pseudo-noise
sequence. The watermark is embedded in a vector
form. Data recovery is done by the means of highpass filter.
A 2D spread
spectrum
Main idea
A watermark pattern S × S is created in the
beginning while this pattern is embedded
alternatively. Around some points will be chosen to
be fixed. After generating the watermark frames
using the host masks the spatial mask will be applied
on them.
A little calculation will be used in
detection algorithm.
CDMA
Method
In CDMA technique one of the four least
significant bit-planes will be replaced by watermark
planes. The random periodic quaternary sequence is
used to select the bit-planes that should be replaced.
This method has more data capacity
for watermark.
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This technique in blind watermarking
technique that embeds a watermark signal
without using host signals will fail.
Don’t specifically protect from the value
of DC blocks.
Fail in facing with statistical attacks
(average frames)
TABLE 3: COMPARISON BETWEEN WATERMARKING METHODS
B. TDC method
As one of the first transformed domain video watermarking
methods (TDC) the work done by Cox et al. in [6] can be
mentioned. This study is concentrated on the importance of
embedding the watermark into perceptually significant
components in order to increase robustness against signal
processing and lossy compression techniques. A non-blind
approach is utilized for watermark detection. The detection is
performed by the original and test frame in the DCT domain,
besides it correlates the difference vector with the expected
watermark pattern.
C. PW method
A perceptual watermarking (PW) method which model
masking properties of the HVS, analyze video sequence or
frames using the mentioned models leads to embed watermark
in the optimal way. The main properties of the HVS named as:
frequency sensitivity, luminance sensitivity, contrast masking,
edge masking and temporal masking, which are exploited by
video watermarking techniques[7, 8].
Spatial domain
Spectral domain
Computational complexity
low
high
Computation time
low
high
Resistance
fragile
resistant
Capacity
high
low
Application
Authentication
Copy control
Due to evaluate more accurate and compare the approaches
and methods, summary of mentioned methods are listed in table
4,5. Table 4 reviews the overall watermarking methods based on
the transformation domain, while table 5 compares the methods
based on their configurations.
A summary of investigation of video watermarking methods
in the frequency domain are depicted in table 2.
TABLE 4: CLASSIFICATION OF METHODS BASED ON WATERMARK
TABLE 2: INVESTIGATION VIDEO WATERMAKING METHODS IN FREQUENCY
EMBEDDING TECHNIQUE
DOMAIN
The watermark of
length n was populated
from a standard normal
distribution apart from
a binary PN sequence
in order to enhance
robustness.
A perceptual
watermarking (PW)
method which models
masking properties of
the HVS, analyzes
video sequence or
frames using the
mentioned models
leads to embed
watermark in the
optimal way.
Showing more
resistance against
attacks in compare
with spatial
domain.
Domain-specific
features (such as
HVS) can be easily
enforced.
method
disadvantages
Complicated
calculations.
Highfrequency
components
tend to
remove in
compression
level.
Pixel domain
approach
advantages
Relatively
high time
complexity
More resistant to
signal processing
techniques and
lossy compression.
Main idea
In this approach,
data will be stored in
source media by
varying the pixel
values using the
computational
methods
Transformation domain
approach
Main idea
First, the host video
transforms by using
frequency domain
methods, then the
transformation
coefficients domain
change for embedding
watermark data.
Finally, the inverse
transformation is used
to obtain the image of
watermarked video.
In this approach,
frequency
transformation will
be applied on host,
for example Discrete
Fourier
Transformation
(DFT) and Discrete
Cosine Transform
(DCT)
Compression domain
approach
PW
TDC
DCT
method
In this approach, the
computational tool is
utilized for
compression in
watermarking. For
example JPEG2000,
MPEG,H.264 and …
compressions.
advantages
disadvantages
simplicity
Fail in blind
watermarking
More resistance
against general
image
processing such
as low-pass
filter, adjust
brightness,
contrast and
blurring the
image
Reduce the
complexity of
Computational
complexity, low
resistance against
some process as
rotation, cropping
and changing size
Poor resistance and
reliability
IV. CONCLUSION
The main goal of this manuscript is to investigate the video
watermarking methods with declaring the strengths and
weaknesses of each method. Of course, each case besides the
weakness is suitable for certain applications in watermarking.
And also, besides the mentioned methods, combining the basic
approaches in this field will lead to increase the efficiency of
proposed algorithm. By considering the expected application
The comparison of watermarking methods using spatial
domain and spectral domain are presented in table 3.
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and investigating event vulnerability, appropriate solution can
be represented due to prepare minimum security requirements.
[4] B. G. Mobasseri, "Exploring CDMA for watermarking of digital video," in
Electronic Imaging'99, 1999, pp. 96-102.
[5] S. Patel, A. Katharotiya, and M. Goyani, "A Survey on Digital Video
Watermarking," International Journal Comp. Tech. Appl, vol. 2, pp. 30153018, 2011.
[6] I. J. Cox, J. Kilian, F. T. Leighton, and T. Shamoon, "Secure spread
spectrum watermarking for multimedia," IEEE transactions on image
processing, vol. 6, pp. 1673-1687, 1997.
[7] R. B. Wolfgang, C. I. Podilchuk, and E. J. Delp, "Perceptual watermarks
for digital images and video," Proceedings of the IEEE, vol. 87, pp. 11081126, 1999.
[8] M. Reid, R. J. Millar, and N. D. Black, "Second-generation image coding:
an overview," ACM Computing Surveys (CSUR), vol. 29, pp. 3-29, 1997.
REFERENCES
[1] T. Jayamalar and V. Radha, "Survey on digital video watermarking
techniques and attacks on watermarks," International Journal of
Engineering Science and Technology, vol. 2, pp. 6963-6967, 2010.
[2] S. Bhattacharya, T. Chattopadhyay, and A. Pal, "A survey on different
video watermarking techniques and comparative analysis with reference to
H. 264/AVC," in 2006 IEEE International Symposium on Consumer
Electronics, 2006, pp. 1-6.
[3] F. H. Hartung and B. Girod, "Digital watermarking of raw and compressed
video," in Advanced Imaging and Network Technologies, 1996, pp. 205213.
TABLE 5: COMPARISION BETWEEN METHODS BASED ON CONFIGURATIONS
approach
Pixel domain approach
Compression domain approach
Transformation domain approach
method
SS
JAWS
resistance
acceptable
acceptable
reliability
acceptable
acceptable
invisibility
good
good
applicability
good
good
Time complexity
good
good
CR
good
good
good
poor
poor
CDMA
acceptable
acceptable
good
acceptable
acceptable
RBEM
VLC
acceptable
poor
acceptable
poor
good
good
acceptable
good
acceptable
good
H.264
TDC
good
good
good
good
good
good
acceptable
acceptable
acceptable
acceptable
PW
acceptable
acceptable
good
acceptable
good
DCT
good
good
good
good
acceptable
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