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

124

COMPARATIVE ANALYSIS OF VARIOUS VIDEO WATERMARKING

TECHNIQUES

Dinesh Goyal1, Shashi Ranjan

2, Dr. Naveen Hemrajani

3*

1, 2

Research 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

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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].

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

Σ (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



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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 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



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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



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Watermarked image

Image 30 Image 58

Scenario 2: Frequency Domain Watermarking (DWT) Input video format MPEG






Original image

Image 1 Image 29

Watermarked frame

Image 30 Image 58



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Scenario 3: Frequency Domain Watermarking (DCT)

Input video format MPEG






Original image

Image 1 Image 29

Watermarked Frames

Image 30 Image 58

PSNR



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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.



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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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50120140506015

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