50120140506015

International Journal of Computer Engineering and Technology (IJCET), ISSN 0976-6367(Print),
ISSN 0976 - 6375(Online), Volume 5, Issue 6, June (2014), pp. 124-135 © IAEME
INTERNATIONAL JOURNAL OF COMPUTER ENGINEERING
TECHNOLOGY (IJCET)
ISSN 0976 – 6367(Print)
ISSN 0976 – 6375(Online)
Volume 5, Issue 6, June (2014), pp. 124-135
© IAEME: www.iaeme.com/IJCET.asp
Journal Impact Factor (2014): 8.5328 (Calculated by GISI)
www.jifactor.com
124

IJCET
© I A E M E
COMPARATIVE ANALYSIS OF VARIOUS VIDEO WATERMARKING
TECHNIQUES
Dinesh Goyal1, Shashi Ranjan2, Dr. Naveen Hemrajani3*
1, 2Research Scholar, Suresh Gyan Vihar University
3*Professor, JECRC University, Jaipur

ABSTRACT
The embedding of a digital signature, or tag data is carried out in the frequency domain. The
high frequency varieties are chosen by any LH and HL in the wavelet domain which are to be
applicable in DCT. Coefficients are changed mid-frequency DCT coefficients such transactions by a
low frequency of the watermark to be embedded. Watermark can be recovered from the video by
selecting a random watermark of any reference framework. The proposed techniques are more
secure, robust and are efficient due to the use of static DCT. Watermark techniques uses a bands HL
and LH for adding watermark where the movement does not impact the quality the extracted
watermark until if the video displays for different types of malware attacks.
In this work we have taken three video watermarking techniques i.e. BIT GET (spatial),
DWT, DCT and one video formats ie.MPEG video to perform a comparative analysis of different
techniques using single video formats, to obtain the best performing technique for video
watermarking. Such that to increase robustness of the video and decrease the embedding time.
Keywords: DWT, DCT, Spatial, Watermarking, Video.
1. INTRODUCTION
Today, the digital media are easily reproduced due to the rapid growth of Internet
technologies and digital watermarking, this is driving an urgent need to solve the problems of
security and protection of copyright. Therefore, the range of the digital watermark is growing
extremely fast in these years [1].
The purpose of a digital watermark is to incorporate auxiliary information into a digital signal
by making small changes that are not perceptible to its recipient. For example, in the case of digital

watermark, the hidden signal should not cause visible or audible distortion. signals allow embedded
invisibly tags are attached to digital documents, watermarks are efficient tools which play a role in
solving the problem of identifying properties in digital growth [2].
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Security in Digital watermarking

The area of video watermarking is mainly due to the problem of robustness to geometric
attacks focused, while the problem of discounting of the more sophisticated attackers. For example, a
common approach to geometric attacks is to resist, to repeat the same watermark in most points in a
video frame.
2. DIGITAL WATERMARKING
Watermark technique is a particular embodiment of the safety of multimedia. Digital
watermarking is defined as a digital signal or pattern inserted into a set of digital data, which can also
be referred to the copyright information. The watermark is a fundamental process in the ownership of
the copyright protection of electronic data, including images, video, audio, etc. The term derives
from the watermark with invisible ink to write secret messages. It is the additional requirement for
robustness of the watermark.
A simple idea of watermark is shown in below Figure. The watermark is a design that is
added to the host signal W watermark signal. The watermark signal, in addition to a function of the
information watermark W ', can also rely on a series of data that is embedded in the key K and, as
shown in Equation 2.1
W=f0(I,K,W’) (2.1)
In watermarking algorithm, the host data I, which is introduced as stego image, watermarking
algorithm and algo watermarks the image with the output image I with watermark W with Equation
2.2:
(2.2)
Control algorithm is a method of extracting the corresponding drawing that retrieves
information watermark signal mixed, perhaps with the help of the key and the original, as shown in
Equation 2.3.
I = g(I, I’,K) (2.3)
2.2 Video Watermarking
Scheme of many watermarking have been proposed in the literature for still images and
movies. Most of them, while other people to insert watermark in compressed video directly to
manipulate uncompressed video, In recent years, researchers tend to study video technology invisible
watermark robust. The extent to which it can be distinguished in view of the domain that are detected
watermark or embedded, which incorporates all of the volumes, real time performance, three axes,
these patterns, resistance to certain types of attack. It is shown in Figure 2.4 Classification map of
existing video watermarking techniques. Can be divided into three main groups based on the domain
in which the watermark is embedded, they spatial region of the base, are property of MPEG encoding
and frequency domain.

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Figure 2.1: Classification map of existing digital video watermark techniques
2.3.1 Spatial Domain Watermarks
Spatial domain watermarking modifies the subset of pixels of one or two randomly selected
images slightly. You can include the start-up, change of the low-order bits each pixel. However,
when you receive the normal supports operations, such as lossy compression or filtering of such
unreliable approach.
First, I review the technique of video watermarking in the spatial domain. Algorithm of this
class has the following characteristics in common:
• A watermark is a domain of coordinates or applied on a pixel-by-pixel.
• No conversion has not been applied to the signal reception in filigree Embed.
• The combination of the host signal, is based on a simple operation, In the pixel domain.
• The watermark can be detected by correlating the expected reason of the received signal
• The watermark can be recognized by correlating the provided Reason of the received signal
• With the help of spread Spectrum modulation the watermark is derived from the message data
Several watermarking methods can be used in the spatial domain. The most basic is to just
flip the lower bits of the selected pixels in a color image or grayscale. This works well only if the
image subject to a change in human or loudness. A more robust watermark embedded in an image in
the same way that a watermark is added to the paper. Such techniques may superimpose a watermark
symbol over an area of the image, and then a fixed value for the intensity of the watermark to the
values of the individual pixels of the image. The resulting watermark can be depending on the value
(large or small, respectively) of the intensity watermark visible or invisible.. One disadvantage of the
spatial domain watermark can crop the image is general operation of the image editor is used to
remove the watermark.
2.3.1.1 Least Significant Bit Modification
LSB encoding is one of the first methods. This can be applied to any form of watermarking
this method, the signal LSB carrier, and is replaced with a watermark. Bits are embedded in the
matrix that serves as a key. There is a need to find new, this sequence is known. Watermark encoder
to select a subset of the pixel values first watermark is inserted. With, the LSB is a built information
of the pixel subset.
The most straight forward of embedding watermark would be to embed a watermark in the
scope of the object at least significant bits. Considering the capacity channel very high to use the
transmission cover the whole, it is possible to incorporate a small object more than once in this
process. Most of these causes, it has been lost due to the attack, but it would be considered one and
only successful survivor watermark.

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2.3.1.2 Correlation-Based Techniques

Another technique for embedding watermark is to use the correlation characteristic of the
additive pseudo-random noise pattern that is applied to the image. According to the formula shown
below in equation 2.4, (x, y) a pseudo-random noise (PN) pattern W is added (x, y) in the cover
image I.
(2.4)
In formula 2.4, k is a gain factor, the image IW watermarked obtained. At the expense of
image quality brand, increasing k increases the robustness of the watermark.
In order to recover the watermark, pseudo-random noise generator with the same algorithm
seeded with the same key, the correlation between the image and the noise model watermarked is
calculated in some cases. If the correlation exceeds a threshold value T constant, the watermark is
detected, a single bit is set. By dividing the image into blocks with ease, this method can extend the
multi-bit watermark, and following the steps described above independently for each block.
This basic algorithm can be improved in various ways. First, the concept of a threshold for
determining a logic 1 or 0 can be solved by using two models of pseudo-random noise was
separated. The model is specified other logical 1 and 0. The above procedure is run once for each
model, we use the model with the highest correlation result. Even after the image has been subjected
to an attack, which increases the probability of correct detection.
2.3.1.3 Patchwork Techniques
The watermark of patchwork, the image is divided into two subsets. A transaction or
characteristics are selected, is applied to a subset of these two in the opposite direction. The subset of
one, if it is increased by a factor k, for example, a subset of the other, the same amount is reduced.
The value of the samples in the subset 'B' and the larger value of b [i] is decreased when the subset
'A' that is, sub-assemblies between the two values of the samples [i] is the difference lead to
intuitively
(a[i]-b[i]) =2N for watermarked images 1=N= = 0 otherwise
2.3.2 Frequency Domain Watermarks
In Frequency domain the secret data are hidden in the lower or middle frequency portions of
the protected image, because the higher frequency portion is more likely to be suppressed by
compression. But how to select the best frequency portions of the image for watermark is another
important and difficult topic. Various frequency domain techniques are as follows:-
Generally DCT, FFT and wavelet transform are used as the methods of data transformation.
In these methods, a watermark that you want to embed general distribution in the domain of the
original data, and the watermark, you almost want to erase, once built. For domain techniques that
has been transformed, they may have a discrete Fourier transform and watermark hierarchical
discrete cosine transform, subband watermarking techniques, or discrete wavelet transforms.
2.3.2.1 Discrete Cosine Transform
It is a process in which a sine wave andof cosine waves converts the sequence of data points
in the spatial domain with different amplitudes in the frequency domain.DCT is a linear transform
that maps an n-dimensional vector a set of n coefficients. For JPEG compression using the DCT, it
for JPEG compression is very robust. However, the method lacks resistance to geometric distortion
strong DCT.

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The most popular domain for image processing is known as Discrete Cosine Transform
(DCT).The DCT image can embed watermark information in the center frequency band of the image
much more easily and can be divided into different frequency bands.The middle frequency bands are
selected so that they are minimized to avoid the most visual major parts of the image (low
frequencies) without much exposing yourself to removal through compression and noise attacks
(high frequencies).
2.3.2.2 Discrete Wavelet Transform
DWT-based methods provide good spatial location and have multiple resolution
characteristics, which are similar to the human visual system. Although this approach shows
robustness to low-pass and median filtering. However, it is not robust to geometric transformations
Possible a different domain for watermark embedding is that of the wavelet domain.. The DWT
(Discrete Wavelet Transform) separates the image into a lower resolution approximation image (LL)
as well as horizontal (HL), vertical (LH) and diagonal (HH) detail components. Then, the process
may be as in the wavelet scale 2 shown below in Figure 2.5, is repeated to calculate a plurality of
scale wavelet decomposition.
One of the most advantages is that it is considered to make it than the DCT or FFT more
accurately to model aspects of HVS as compared with the wavelet transform. This allows us to
utilize higher energy watermarks in regions that the HVS is known to be less sensitive to, such as
high-resolution detail bands LH, HL, HH). Embedding watermarks in these regions allows us to
increase the robustness of our watermark, at little or no additional impact on image quality.
Figure 2.2: 2 Scale 2-Dimensional Discrete Wavelet Transform
The discrete wavelet transform (DWT) is based on sub-band coding, was found to give a
quick calculation of wavelet transform. It is easy to implement and reduces the time and computing
resources. Techniques to decompose discrete time signals were prepared foundations of the DWT go
back to 1976. Similar work was nominated sub-band coding was done in the speech signal coding. In
1983, sub-band coding is a technique similar to the pyramid was developed, which was named
coding. After a number of improvements efficient multi-resolution analysis schemes were made for
these coding schemes.
2.3.2.3 Discrete Fourier Transform
It is translation invariant and rotation resistant, leading to strong robustness to geometrical
translated attacks.DFT uses complex numbers, while the DCT uses only real numbers.
Barni M. et al a robust watermarking approach for raw video in [87]. This approach first
extracts the brightness of the to-be-tagged frames, calculation of its full-frame DFT and then with the
size of the coefficients. The watermark is composed of two alphanumeric strings. The DFT
coefficient is changed, then the IDFT.. Only the first frame of each GOP provided watermark, which
was composed of twelve frames, so that the others who undamaged. It's good robustness of the
conventional image processing as linear / non-linear filtering, sharpening, to resist JPEG

compression, and geometric transformations such as scaling, rotating, and cropping. May decide to
provide one or more frames in GOP watermark, a trade-off between time for the marking and the
degree of robustness for the sequence spent required to achieve.
2.4 Essential Ingredients for Video Watermarking
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The watermarking systems can be characterized by a set of properties that define, including
incorporation efficiency, fidelity, data payload, blind or informed detection, robustness, security and
key encrypted watermark, change watermark and multiple, cost, handling strength, low presence,
early detection, unambiguous, false positive rate, sensitivity and scalability. The relative importance
of each property depends on the requirement of the application and the role it will play the
watermark. Some of them are common to more practical applications. In this section, the general
requirements are listed and briefly discussed. The analysis is focused on image and video watermark.
2.4.1 Fidelity
The first requirement would be that is fidelity. A watermarking system is of no use to anyone
else if the cover image is distorted to the point of being useless, or even annoying. Ideally the image
watermark should be perceptually visible in high quality equipment’s.
2.4.2 Robustness
The brand ideal watermark should be very robust, totally resistant to distortion introduced
either during normal use, ie, intentional attack, or a deliberate attempt to disable or remove the
watermark present, namely the intentional attack or malicious Deliberate attacks involving
transformations that are commonly applied to images during normal, such as cropping, resizing,
contrast enhancement use. . etc.
Robustness is the resilience of the embedded watermark against removal by the signal
processing. The use of music, pictures and video signals in digital format, commonly involves many
kinds of distortions, such as lossy compression, or, in the case of images, filtering, scaling, contrast
enhancement, cropping, rotation, etc. In order to watermarks to be useful, the brand should be
detectable even after such distortions have occurred. It is widely accepted that robustness against
signal distortion is best achieved if the watermark is placed in perceptually important parts of the
signal. This depends on the behavior of the lossy compression algorithms that operate by removing
the perceptually insignificant data does not affect the quality of the compressed image, audio or
video.
Most watermarking scheme based video watermarking techniques image. However, water
marking video presents some issues that are not present in the image watermarking. Video signals
are very susceptible to attack by pirates, including within the media, frame dropping, frame shift,
statistical analysis, interpolation, etc.
2.4.3 Use of Keys
Another property of a marking system is ideal that implements the use of passwords to ensure
that the focus does not become useless when the algorithm is aware [22]. It can also be a goal that
the system uses an asymmetric key cryptographic system, such as public / private key. Although
private key systems are fairly easy to apply watermarks, asymmetric key pairs generally are not. The
risk here is that integrated systems watermark might have discovered the private key, ruin the
security of the entire system. This was exactly the case in which a single DVD decoder application
on the left is the secret key that is not encrypted, in violation of the entire mechanism of DVD copy
protection.

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2.4.4 Blind Detection

Blind detection refers to the ability to detect watermarks without access to the original
document. Due to the large file sizes of compressed video and the difficulty of indexing them to find
a specific frame, it is particularly important in video watermark requirement.
2.4.5 Capacity and Speed
Somewhat less important requirements of a marking system can be ideal capacity and speed.
A watermark system should allow a useful amount of information to be embedded in the image. This
can range from a single bit all the way up to several paragraphs of text. Moreover, in the systems for
embedded water marks, detection of watermarks (or embedding) may not be too computationally
intensive to avoid its use in low cost microcontrollers
Capacity is the amount of information that can be expressed by a watermark embedded water.
The theoretical capacity of embedded water marks was examined using the theoretical concepts of
information. Depending on the application at hand, the algorithm of the watermark should allow a
predetermined number of bits to hide.
2.4.6 Statistical Imperceptibility
The last possible need an ideal marking system is the statistical watermark imperceptibility.
The algorithm of watermark bits must modify the lid so that the statistics of the image are not
modified in any way detector may betray the presence of a watermark. This requirement is not as
important as in steganography, but some applications may require it.
2.4.7 Low Error Probability
Even in the absence of attacks and distortions of the signal, the probability of not detecting
the watermark, i.e, false negatives, and detects a watermark, when, in fact, one does not exist, i.e,
false positives should be very small. In general, the statistically based algorithms have no problem to
meet this need, however, this possibility should be shown, if the watermark is legally enforceable.
2.4.8 Real-time Detector Complexity
For watermarks consumer-oriented applications, it is important that the complexity of the
algorithms for the detection and extraction is low enough to be performed within the time specified
in real time
3. VIDEO WATERMARKING
It appears each image watermarking method can also be emulsified to video watermarking,
whereas video watermarking technique ought to overcome a further task such as an image
watermarking method. Certain video features that impact watermarking comprises:
• High association betwixt successive frames. I fliberated watermarks are implanted in every
frame, an attacker could run average frame to get rid of vital portions of the watermark
embedded.
• Applications, such as monitoring of transmissions necessitate real-time processing, and thus
should have little difficulty.
• Imbalance in among the regions of motion and real estate.
The watermarked video footage is extremely disposed to malicious assaults, like average frame,
frame exchange, statistical analysis, digital-to-analog (AD / DA) conversions and lossy compressions

131
4. EXPERIMENTS AND RESULTS

To conduct the experiment MATLAB has been used which provides a structure that consists
of information about the AVI file delivered as a parameter field, while the function aviinfo reads
images or AVI movies MATLAB the preservation of the structure Movie it is employed for. And can
be constructed to recite video information from a multimedia file formats various functions
employed mmreader as a multimedia reader object.
Processing of video files comprises of the subsequent steps:
1. In this step the frame is being converted into an image using frame2im function.
2. In this processing of image starts.
3. In the last step the result is being converted rear into a frame employing im2frame function.
Experimental Setup
The system having following configurations
HP model laptop having following configuration
OS Name Microsoft Windows 7
Processor core to dual
Installed RAM 2 GB
Total RAM 1.76 GB
Available RAM 999MB
Scenario 1: Spatial Domain Watermarking (BITGET)
Input video format MPEG
Output Video format IV50
Number of frames taken 29
Watermark size 60 x 60
Video frame size 352 x 544
Time to embed watermark 35.5526 sec
Original image
Image 1 image 29

132
Watermarked image

Image 30 Image 58
Scenario 2: Frequency Domain Watermarking (DWT)
Original image
Image 1 Image 29
Watermarked frame
Image 30 Image 58

Scenario 3: Frequency Domain Watermarking (DCT)
133
Original image

Image 1 Image 29
Watermarked Frames
Image 30 Image 58
PSNR

134
RESULT ANALYSIS

In this the results of three genres of the video watermarked techniques using BIT GET, DCT ,
DWT and taking a single video formats i.e., MPEG and hence compared with their respective results.
The results shown in the previous chapter are taken after performing chaotic map based selective
watermarking on video.
1. In this toil the MPEG video is represented by the blue line where the normal input video is
watermarked using selective watermarking technique i.e. BITGET technique that produces a
chaotic map.
2. The green line shows DCT watermarking technique for chaotic map.
3. The red line shows DWT watermarking technique for chaotic map.
Fig: - PSNR ratio of different techniques
The above line shows the watermarking variation among the three videos watermarked
techniques the blue line shows BIT GET, green shows DCT and red one shows DWT.
As output comes, it demonstrates that the PSNR of starting frames of DWT is higher and that
of BIT GET is lower but as the frames increases the PSNR values of DWT decreases and that of BIT
GET increases, Hence the PSNR value of BIT GET is better than DCT and DWT.
CONCLUSION
Digital Watermarking has been the need of the hour in all digital multimedia applications in
sequence to ensure confidentiality and integrity of the content shared online in the present era.
Various Digital Watermarking techniques exist, namely BITGET, DCT AND DWT.
Multimedia can be an image, audio or a Video, which has been time and again watermarked
using above techniques, but the results of the same vary as per the type and quality of multimedia.
Video is the most shared multimedia in present scenario, many video codecs also exist in the
present era for ensuring better quality of delivery, but while ensuring their integrity and
confidentiality the quality is deteriorating.
It can thus be concluded that high compressed codecs like MPEG and further are better
adapted to frequency watermarking than that of spatial watermarking, because spatial watermarking
creates impact on image data.
Spatial Watermarking is better for uncompressed videos and Frequency watermarking is
better for compressed video.

135

At the end one can easily say the spatial watermarking is better as it consumes less time and
has low noise, at the same time in comparison of DWT DCT, DWT stands a better one on the
same parameters. But if parameter is payload capacity then DWT is better than DCT BITGET.
FUTURE WORK
In future the same work can be carried out with frequency watermarking in different video
formats and also a comparative study may be done for different type of video watermarking
techniques for single mpeg video formats.
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