Abstract- In the present time, security  int content of multimedia became one of
significant science types. Watermarking is one type of multimedia protection,
it is idea of protect digital components. Watermarking has extended and applied
for many requirements , like fingerprinting, copyright protection, content
indexing and many others watermarking application.

The suggested algorithm is to hide a bio-watermarking encrypted
data using video file as a cover. Where the recipient will need only to follow
the required steps to retrieve the data of watermark. The idea of proposed method
is based on hiding the watermark in audio partition of video file instead of video’s
image. Also use multiple frequency domains to hide the biometric watermark data
using chaotic stream as key for encrypting the watermark and choose location for hiding. Subjective
and objective tests (SNR, PSNR and MSE) are used to estimate the performance of the suggested
method with applying simple attack that may attack the cover file.

Experimental result of the algorithm shows good recovering of watermark
code which is virtually undetectable within video file.

Keywords: video watermarking, DCT, DWT, Biometric system, chaotic.
 

I.       
Introduction

Nowadays,
the digital media and the Internet have become so popular. That led to rise  the requirements of secure data transmission.
A number of useful  techniques are
proposed and already in use 1. Watermark is  one of these techniques which is a digital code embedded
into the content of digital cover i.e. text, image ,  audio or video sequence 2.

Watermarking method is describe in the process as follows: Firstly,
the abstraction of copyright data in the form of watermarks and imbedded in multimedia
carriers using one of many embedding algorithms. After that, these carriers are
distributed by the network or  any digital
storage. When necessary , the carriers are processed to detect the watermark existence
. It is also  possible to extract watermark
for many various  purposes3.

In general,  watermarking process
is to embed some copyright data into the host data as  an evidence ownership right. It must meet
requirements which is: Security Obviously, Robustness, Imperceptibility and
Capacity 4.

Various algorithms of digital video watermarking have
been suggested. These  techniques are categorized
 according to the domain which they
working with. Some of these techniques embedded the watermark using  the spatial domain using modification of  the pixel values in each extracted video
frame. These methods are entrusted to attacks and signal distortions. However,
other techniques  using the frequency
domain to embed their watermark, this is the better robust to distortions2.

Digital video is a sequence of still images merging with audio. The
watermark will carry all types of  information however the quantity of watermark
data is limited. The vulnerability of the data is direct concerning of  the amount of the  information that carried by the watermark. The
amount is absolutely limited by the size of particular video sequence2.

 

II. What
is biometrics?

Biometrics, is the process of  authentication  which depend on the  physiological or behavioral properties and its
ability to identify whether the person is authorized or not. Biometric properties
distinctive as they cann’t be lost or forgotten, the presentation of  identifying  person will be bone physically 56.

There are many of  biometrics like fingerprint, face, hand
thermogram, , signature, retina, iris, hand geometry, voice and so… .The most
proven method is Iris -based identification . Iris can be  defined as the colored part of eye, Fig. 1 shows the iris contents .The two eyes iris of any person have various
iris pattern. Because the iris has a lot of  characteristic which help to distinguish one
iris from another, two conformable twins also have various iris patterns. Iris  stills in a stable pattern not depended to the
age affection  that mean it stay in
stability from the birth to the death. Also, the system of  iris recognition can be un-invasive to their
user57.

III.  
Chaotic signal

The chaotic signal is similar 
to noise signal,  but it is
certain in complete, that means if anyone has the initial values and the used function,
that will be reproduce the same amount exactly. The profit of chaotic signal
are:8

I.        
The initial conditions sensitivity

A minor variation in initial amount will cause important distinction
in subsequent measures. The final signal will be differ completely  if there is a small modification in the signal
amount.  

II.      
The accidental feature apparently

To compare with productive casual natural number in
which the numbers scope cannot be generated again, the technique used for generating the same casual number
in methods based on the chaotic function will create the ground that if the
initial values and the used function are the same, the same number generated
again.

III.     The
work deterministic

However, the chaotic functions were the casual manifest, they are wholly
similar. That is if the initial values and the used function are fixed, the
amounts of numbers will generate and re generate which seemingly have not any
order and system. Logistic Map signal is one of the farthest known chaotic signals,
this signal is presented by equation shown in (1):

Xn+1
=rXn (B-xn)                  (1)

in which the Xn will get
the numbers between 0,1. The signal shows three different chaotic features in
three different ranges on the division of 
r parameter of which the signal feature will be the best by considering
X0 =0.3.

·        
if  r 0,3, then the signal feature in the first 10 repetition
show some chaos and after that it was fixed , Fig. 2 (a)910

·        
– if  r  3, 3.57, then the
signal feature in the first 20 repetition show some chaos and after that it was
fixed, Fig. 2(b),

·        
– if   r   3.57,4, then the
signal feature is completely chaotic , Fig. 2(c)

According to the given
description and research requirements for complete chaotic feature for video watermarking,
the logistic map chaotic signal with primary value X0=0.3 and r ? 3.57, 4 are
used9.

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

IV.   
The related Works

There are many of video
watermarking methods proposed in last period  either  in the spatial domain  or the frequency domain. One of these methods
was proposed by Mobasseri (2000), who suggest a watermarking algorithm for
compressed videos in spatial domain. Where Hong et al (2001) proposed DWT based
algorithm in which middle frequencies are modified and a flag is generated for
extraction process. In other side Liu et al (2002) proposed a video
watermarking method based on wavelet transform where multiple information bits
are embedded into uncompressed video sequences. Ge and other (2003) find a adaptive
algorithm to video watermarking based on Wavelet packet transform-based robust
video watermarking method. Chang & Tsai (2004) proposed a watermarking
scheme for a compressed video sequence via VLC decoding and VLC code
substitution. Zhong & Huang (2006) have presented video watermarking based
on spread-spectrum techniques to improve watermarking robustness. Mirza et al
(2007) proposed a video watermarking scheme based on Principal Component Analysis 4.

V.     
The proposed  method

As we know video file format contain major two part of multimedia
types: image and audio. It is generated by mixing the two kinds of multimedia
types. The proposed method differs from the typical watermarking scheme. It is
based on hiding watermark data in video’s audio part instead of image one. 

There are two categories of Digital watermarking technique:
spatial domain watermarking technique and frequency domain watermarking
techniques. The spatial domain methods hide the watermark using  modifying some values of video file in directly
way . The frequency domain technique will be embedding  the watermark in best ways because of better to determine perception
criterion. Therefore the proposed algorithm used frequency domain to
hide watermark data and in order to achieve more security multiple type of
frequency domains with chaotic key are used.

In the proposed method, the watermark is based on biometrics
(exactly on iris) to generate the watermarking code. The following sections
discuss the proposed video Watermarking in details.

A)            
 The proposed algorithm of embedding watermark
code:

The proposed algorithm can be divided into two basic parts: generating
the biometric watermark code and hiding it in video file data using chaotic key.

·        
Generating the
biometric watermarking code:

Iris region consists of two
circles: one for iris sclera boundary and another for iris pupil boundary. To
isolate actual iris region in eye image, segmentation is required. To have
segmentation, edge detection, circle detection, eyelid detection are required.
Various methods for edge detection are available. Here, canny edge detection is
used to find edges and Hough transform to find iris and pupil boundaries from
the image. CASIA iris image database is
used for experimentation. Iris image must be available in sender and receiver sides. For
more security the watermark is encrypted using chaotic key.

The
proposed algorithm of generating the bio-watermarking code is explained in the following
steps:

Input: Iris image.

Output: Encrypted bio-watermarking code.

1)   
Begin

2)   
Choose iris image.

3)   
Apply iris segmentation.

4)   
Take iris data which is laying under
pupil circle. 

5)   
Apply edge detection using canny
filter.

6)   
Generate chaotic key.

7)   
Encrypt iris data using the
generated chaotic key.

8)   
End.

Fig. 3 shows the flowcharts of generating the bio-watermark code.

 

 

 

 

 

 

 

 

 

 

 

 

 

 

·        
Embedding the
watermark in video file using chaotic key:

     Input: Video file,
Bio-watermark code.

     Output: Watermarked video
file.

1)      
Begin.

2)      
Choose video file to be cover file.

3)      
Split image and audio in it and
consider audio part as a cover.

4)      
Apply DWT on audio part.

5)      
Apply DCT on resulted DWT
coefficients.

6)      
Hide the length of watermark (Len)
in first 4 bytes of cover data.

7)      
Generate chaotic key to be the index
of chosen cover data .

8)      
Hide watermark code in cover by
exchanging the fourth decimal number after comma in cover by another digit of
watermark code.

9)      
Repeat this step until last digit in
watermark code.

10)  
Apply DCT inverse, then DWT inverse.

11)  
Reformat  the video cover.

12)  
End

 

Fig. 4 shows the proposed algorithm of hiding the
biometric watermarking code in video file using chaotic key.

B)            
The proposed
algorithm of extracting watermark code:

Input: The covered video file.   

Output: Achieve video file protection or not.

1)      
Begin.

2)      
Input the covered video file.

3)      
Extract audio part from the covered
video file.

4)      
Apply DWT on audio part.

5)      
Apply DCT on resulted DWT
coefficients

6)      
Extract the length (Len) of
watermark from first 4 byte in cover.

7)      
Generate chaotic key(for extracting
and decryption operation).

8)      
Using the chaotic key to extract
watermark code.

9)      
Repeat this step until reaching the
length of watermark code.

10)  
 Decrypt the extracted watermark using same
chaotic key.

11)  
 Independently… Generate the iris watermark
code (origin one) by executing the steps of generating the biometric watermark
(1 to 5).

12)  
Compare
the extracted watermark with the original one. If they are identical ,video file
protection is achieved otherwise the file is not protected.

13)  
End

Fig.5 shows the proposed algorithm of
extracting watermark code.

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

VI.   
experimental application and results

A number of video
sequences have been tested using the proposed method. The bio-watermark is
extracted from the watermarked video and its robustness is checked by calculating
some famous measures.

Moreover,
the proposed method is applied on many iris images obtained from CASIA
database. At last the iris code is obtained and hidden in video file. Figs
6,7,8 show the experimental steps that are done on iris image to get bio-watermark
code.

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

A number of measures are
applied on it to make sure that the proposed algorithm is strong enough to
carry the watermark safely. Table I. explain the results of applying standard measures
(Correlation, SNR,PSNR and MSE)  to the proposed
algorithm.

 

table I. the
results of applying standard measures to proposed algorithm

File name

Correlation

SNR

PSNR

MSE

Radar

1

219.3514

75.586

2.7631e-08

Morale

1

205.74

75.504

2.8152e-08

Test

1

212.03

75.826

2.6145e-08

 

 The watermarked video was attacked by simple
types of watermarking attacks. These attacks attempt to damage the embedded watermark by modifications
of the whole cover without any effort to identify and isolate the watermark 1112.
Adding white noise (Gaussian noise) is applied to the video cover resulting from
the proposed algorithm. Fig. 9 shows the effect of adding Gaussian noise to the
video cover file with different signal to noise ratio values. While Table II.
explains the output results of adding Gaussian noise to the video cover .

 

 

 

Table II. The
output result of adding gaussian noise to the embedded watermark

SNR

Correlation

MSE

200

1

0

150

1

0

134

0.8720

0.0743

120

0.7956

0.4149

100

0.1926

3.7147

90

0.0626

9.2799

75

0.0537

30.0978

 

VII. conclusion

The paper propose an
efficient method to embed abiometric watermarking in video file. It make use of
two powerful mathematical transforms: 
DWT and DCT and applied them on the audio part of video file format
instead of video’s images. The proposed method use the chaotic sequence in
order to find a video file locations in order to hide bio-watermark on the one
hand and the sequence is used  to encrypt
and decrypt the bio-watermark data on the other.

After
applying the proposed algorithm, the similarity between the original watermark and the extracted
watermark from video files is measured using correlation, SNR, PSNR and
MSE. Also measures are applied on attacked video file using correlation and
MSE. The experimental results show their robustness against noise adding; very
low noise watermark with expectable SNR values. The obtained results give to
the proposed algorithm high performance
with robustness in watermarking application in order to achieve protection to
any video file.

Reference

 

1. Bhaumik Arup , Choi  Minkyu ,Robles Rosslin J. and Balitanes
Maricel O. ,” Data Hiding in Video”, International Journal of
Database Theory and Application, Vol. 2, No. 2, June 2009, p 9-16 .

2. Hood Ankita A. and  Janwe 
N. J. ,”Robust Video Watermarking Techniques and Attacks on
Watermark – A Review”, International Journal of Computer Trends and
Technology- volume4 Issue1 ,2013, p30-34.

3. Faragallah  Osama S., “Efficient video watermarking
based on singular value decomposition in the discrete wavelet transform
domain”, International Journal of Electronics and Communications (AE?) , Int.
J. Electron. Commun. (AE?) 67 , 2013 , p189– 196 .

4. Bhatnagar Gaurav and Raman
Balasubrmanian, “Wavelet packet transform-based robust video watermarking
technique”, Indian Academy of Sciences , Sadhana  Vol. 37, Part 3,  2012, p 371–388. 

5. Al-Gurairi  Maha Abdul-Rhman Hasso,” Biometric
Identification Based on Improved Iris Recognition Techniques”, A Ph. D.
Thesis Submitted to The Council of the College of Computer and Mathematical
Sciences, University of Mosul ,2006.

6. Waghmare L.M. and Roselin
Vanaja, ” Iris Texture Analysis for Security Systems” , International
Journal of Computer Applications (0975 – 8887) Volume 64– No.22, 2013, p37-44.

7. Dhavale Sunita V. ,”
DWT and DCT based Robust Iris Feature Extraction and Recognition Algorithm for
Biometric Personal Identification “, International Journal of Computer
Applications (0975– 8887) Volume 40– No.7,  2012, p 33-37.

8 Enayatifar R. , Mahmoudi
F. and Mirzaei K.,” Using the chaotic map in image steganography.
International Conference on Information Management and Engineering, 2009 ,p 491-495.

9. Saeed  Melad J., ” A New technique based on
chaotic steganography and encryption text in  DCT domain for color image”, Journal of
Engineering Science and Technology Vol. 8, No. 5 , 2013, p508 – 520 .

10.Ahmed  H.E.,  Kalash, H.M. and Farag Allah, O.S., “An
efficient chaos-based feedback stream cipher (ECBFSC) for image encryption and
decryption”, Informatica, 31(1), 2007 ,p 121-129.

11. Ali Dujan Basheer Taha ,
“Digital Image Watermarking Techniques For Copyright Protection”, A
Ph. D.  Thesis Submitted to The Council
of the College of Computer Sciences & Mathematics , University of Mosul. ,
2004.

12.Zlomek  Martin, ” Video Watermarking”,
master thesis submitted to Department of Software and  Computer Science Education,  Charles University in Prague , Faculty of
Mathematics and Abstract- In the present time, security  int content of multimedia became one of
significant science types. Watermarking is one type of multimedia protection,
it is idea of protect digital components. Watermarking has extended and applied
for many requirements , like fingerprinting, copyright protection, content
indexing and many others watermarking application.

The suggested algorithm is to hide a bio-watermarking encrypted
data using video file as a cover. Where the recipient will need only to follow
the required steps to retrieve the data of watermark. The idea of proposed method
is based on hiding the watermark in audio partition of video file instead of video’s
image. Also use multiple frequency domains to hide the biometric watermark data
using chaotic stream as key for encrypting the watermark and choose location for hiding. Subjective
and objective tests (SNR, PSNR and MSE) are used to estimate the performance of the suggested
method with applying simple attack that may attack the cover file.

Experimental result of the algorithm shows good recovering of watermark
code which is virtually undetectable within video file.

Keywords: video watermarking, DCT, DWT, Biometric system, chaotic.