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.
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
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
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
data into the host data as an evidence ownership
right. It must meet requirements which is: Security
Obviously, Robustness, Imperceptibility and Capacity 4.
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
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
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.
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
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
The initial conditions
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
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
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):
=rXn (B-xn) (1)
Where Xn gets the
numbers in range 0,1. The signal explain three various chaotic characteristics
in three various ranges on the division of r parameter , the signal characteristics
be the best by assuming X0 =0.3.
in r 0,3, the signal characteristics in the
first 10 iteration show some chaos and they were fixed after that
, Fig. 2 (a)910
in r 3, 3.57, the
characteristics in the first 20 iteration show some
chaos , they were
fixed after that, Fig. 2(b),
in r 3.57,4, the
characteristics are chaotic in
complete, Fig. 2(c)
Agreement with the above
description and the requirements of the proposed algorithm to
ensure complete chaotic characteristics for video watermarking,
the logistic map chaotic signal with primary value X0=0.3 and r ? 3.57, 4 are
The related Works
There are many of watermarking methods based on video file as cover suggested in last
period . One of these methods was proposed by Mobasseri (2000), who
suggest a watermarking algorithm in compressed videos using spatial domain. Where Hong et al (2001)
proposed an algorithm based on DWT they modify
frequencies .In other side Liu et al (2002)
suggested a video watermarking algorithm using DWT to
embed multi information bits. Chang
& Tsai (2004) suggested a watermarking algorithm for a compressed
video by VLC decoding and VLC code substitution. Zhong &
Huang (2006) suggested video watermarking schema
using spread-spectrum method for watermarking robustness
improvement. Mirza et al (2007) suggest a video
watermarking method using Principal Component Analysis
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 to ensure better determine of perception criterion
and robust watermarking. 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.
The proposed algorithm of embedding
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:
To generate iris watermark data the iris (included in eye image) must
be segmented .This
will be made in the following steps : edge detection, circle
detection and eyelid detection. There are many technique
edge detection. This paper used canny edge detection and Hough transform to find iris and pupil boundaries. 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.
data which is laying under pupil circle.
edge detection using canny filter.
iris data using the generated chaotic key.
Fig. 3 shows the flowcharts of generating the bio-watermark code.
Embedding the watermark in video file using chaotic key:
Input: Video file,
Output: Watermarked video
video file to be cover file.
3) Split image and audio in it and consider audio
part as a cover.
DWT on audio part.
DCT on resulted DWT coefficients.
the length of watermark (Len) in first 4 bytes of cover data.
chaotic key to be the index of chosen cover data .
watermark code in cover by exchanging the fourth decimal number after comma in
cover by another digit of watermark code.
this step until last digit in watermark code.
DCT inverse, then DWT inverse.
the video cover.
Fig. 4 shows the proposed algorithm of hiding the
biometric watermarking code in video file using chaotic key.
The proposed algorithm of extracting watermark code:
Input: The covered video file.
Output: Achieve video file protection or not.
the covered video file.
audio part from the covered video file.
DWT on audio part.
DCT on resulted DWT coefficients
the length (Len) of watermark from first 4 byte in cover.
chaotic key(for extracting and decryption operation).
the chaotic key to extract watermark code.
this step until reaching the length of watermark code.
Decrypt the extracted watermark using same
Independently… Generate the iris watermark
code (origin one) by executing the steps of generating the biometric watermark
(1 to 5).
coparition between the onigin watermark with the extracted watermark data. If they are identical ,video file protection is achieved otherwise
the file is not protected.
Fig.5 shows the proposed algorithm of
extracting watermark code.
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.
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
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
table I. the
results of applying standard measures to proposed algorithm
The watermarked video was attacked by simple
types of watermarking attacks. This types of attacks are try to annoy the
watermark by modify the whole cover without any attempt of identifying and
separating 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
The paper propose an
efficient method to embed a biometric 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.
applying the proposed algorithm, some
standard measures between the two watermarks( original and extracted one) are
applied using correlation, SNR, PSNR and MSE. Also measures are applied on the 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.
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