1. International Journal of Computer Engineering and Technology (IJCET), ISSN 0976-6367(Print),
ISSN 0976 – 6375(Online) Volume 4, Issue 4, July-August (2013), © IAEME
240
INFORMATION HIDING IN EDGE LOCATION OF VIDEO USING
AMALGAMATE FFT AND CUBIC SPLINE
1
Dr. Hanaa M. A. Salman
Computer Science Department, University of Technology, Baghdad
ABSTRACT
This paper presents the concealment of information based on the use videos as a cover to hide
the existence of the secret message. The secret message is encrypted using RSA before being
embedded in the cover video. This encrypted secret message is then embedded in predetermine
locations using Lest Significant Bits (LSB), and real part of Fast Fourier Transform (FFT). Finally
inverse Discrete Fourier Transform (IDFT) is applied. The locations are cubic spline control points
which are derived from detection the edge upon using (prewitt and canny). These control points are
dynamically changed with each video frame to reduce the possibility of statistically identifying the
locations of the secret message bits, even if the original cover video is made available to the
interceptor. The proposed method is evaluated in terms of the Average Peak Signal to Noise Ratio
(APSNR), as well as the Average Mean Square Error (AMSE) measured between the original and
steganography video. Results show minimal degradation of the steganography video for secret
message.
Keywords: Video steganography, Edge detection, FFT, Cubic spline, PSNR, AMSE
1. INTRODUCTION
One of the most important challenges facing the process of sending and displaying the hidden
information, especially in public places is the presence of the intruder. The intruder starts to
processes such as Interruption, modification, fabrication and Interception. One of the solutions to this
problem is to use steganography. Steganography is a process of hiding information in cover media,
in a way to keep others from thinking that the information even exists. There are basically three
types[1] of steganography protocols used, these are: Pure Steganography, Secret Key Steganography,
Public Key Steganography. Steganography is mad of three parties: sender, receiver, and
communication channel. The sender performs the embedding process over the carrier by using the
secret information and the key to generate the stego-carrier. The receiver performs the extraction
process over the stego-carrier by using the key to extract the secret information. The channel, it
INTERNATIONAL JOURNAL OF COMPUTER ENGINEERING &
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ISSN 0976 – 6367(Print)
ISSN 0976 – 6375(Online)
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2. International Journal of Computer Engineering and Technology (IJCET), ISSN 0976-6367(Print),
ISSN 0976 – 6375(Online) Volume 4, Issue 4, July-August (2013), © IAEME
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provides secure communicating between parties. Steganography [2] was normally combined with
cryptography to further add another layer of security.
A video file is generally a collection of images and sounds. The great advantages of video are
the large amount of data that can be hidden inside and the fact that it is a moving stream of images
and sounds. Therefore, any small but otherwise notice able distortions might go by unobserved by
humans because of the continuous flow of information [3].Video steganography methods are broadly
classified into (temporal domain and spatial domain), or (compressed video, and uncompressed
video).
Several researchers have addressed the problem of video steganography.
In [4] a comparative analysis between Picture (JPEG) steganography and Video (AVI)
steganography by quality and size was performed. The authors propose to increase the strength of the
key by using UTF-32 encoding in the swapping algorithm and lossless steganoraphic technique in
the AVI file. However, payload capacity is low.
In [5] an adaptive invertible information hiding method for Moving Picture Expert Group
(MPEG) video is proposed. Hidden data can be recovered without requiring the destination to have a
prior copy of the covert video and the original MPEG video data can be recovered if needed. This
technique works in frequency domain only. It has the advantages of low complexity and low visual
distortion for covert communication applications. However, it suffers from low payload capacity.
In[6], presents a steganoraphic model which utilizes cover video files to conceal the presence
of other sensitive data regardless of its format. The model presented is based on pixel-wise
manipulation of colored raw video files to embed the secret data. The secret message is segmented
into blocks prior to being embedded in the cover video. These blocks are then embedded in pseudo
random locations. The locations are derived from a re-orderings of a mutually agreed upon secret
key. Furthermore, the re-ordering is dynamically changed with each video frame to reduce the
possibility of statistically identifying the locations of the secret message blocks, even if the original
cover video is made available to the interceptor. The author also presents a quantitative evaluation of
the model using four types of secret data. The model is evaluated in terms of both the average
reduction in Peak Signal to Noise Ratio (PSNR) compared to the original cover video; as well as the
Mean Square Error (MSE) measured between the original and steganoraphic files averaged over all
video frames. Results show minimal degradation of the steganoraphic video file for all types of data,
and for various sizes of the secret messages. Finally, an estimate of the embedding capacity of a
video file is presented
In [7] authors search how the edges of the images can be used to hiding text message in gray
image. The authors tried to give the depth view of image steganography and Edge detection Filter
techniques.
In [8] authors proposed a new technique using the motion vector, to hide the data in the
moving objects. Moreover, to enhance the security of the data, the data is encrypted by using the
AES algorithm and then hided. The data is hided in the horizontal and the vertical components of the
moving objects. The PSNR value is calculated so that the quality of the video after the data hiding is
evaluated.
In [9] authors describe how motion vector can be used as a carrier to hide data. The secret
message bit stream is first encrypted by using RSA algorithm and the encrypted is embedded in the
least significant bit by using Least Significant Bit and also use edge detection mechanism for
selecting the pixel. The performance is calculated by using Peak to Signal Noise Ratio. The
performance analysis shows that the algorithm ensures better security against attackers
An amalgamate method of Parametric Spline and DFT for video steganography is applied,
instead of embedding secret information in all over the selected frame of video, an edge detection is
applied followed by a curve selection method is applied as positions where, the secret bits to be

3. International Journal of Computer Engineering and Technology (IJCET), ISSN 0976-6367(Print),
ISSN 0976 – 6375(Online) Volume 4, Issue 4, July-August (2013), © IAEME
242
embedding. Thus if the intruder knows the set of control points it may lead to discover the secret
message. An improvement is made by: 1. Extraction the intensity values of pixels for these control
points along the frame of video. 2. Applying the DFT for the result intensity vector values. 3.
Embedding information into the LSB's of the real part of DFT. 4. Apply IDFT. This paper is
organized as follows: Section 2 introduces the proposed video based steganoraphic algorithm, and
then presents the steps of embedding and extraction process. Section 3 presents the experimental
results and finally, conclusions and future work are presented in section 4.
2. PROPOSED ALGORITHM
The proposed video steganoraphic scheme is based on locations of the cubic spline
interpolation control points over the hybrid edge detection methods; the Prewitt and the Canny. This
proposed method consist of embedding phase as presented in section 3.1, and extraction phase as
presented in section 3.2
3.1 EMBEDING PHASE
The input to this phase is: secret message, video as cove media, and RSA public key of the
receiver, while the output is the stego video. The block diagram of the embedding phase is shown in
Figure (1), and the algorithm consists of the following steps described below.
Step1: Secret message processing: convert the secret message into digits using Table (1). Apply
RSAencryption algorithm as in [9].
Step2: Cover video processing: Split the cover video into a sequence of frames, each video frame
dimension is H ×W Pixels. For each randomly selected frame convert into grayscale frame, then
apply edge detection using (Prewitt and Canny) algorithm as in [8, 7, 9]. Apply cubic spline
interpolation algorithm as in [10] over the generated edge. Find control points to the generated cubic
spline curve. Determined pixels value that corresponding location of these control points over the
input frame.
Step3: Embed processing: While the extracted frame pixels is not empty get the extracted frame
byte .While the hidden message bits, is not empty get a bit and assigned it to the first bit of the real
part of the DFT of the frame byte. Apply the IDFT. End of while hidden message. End of while
extracted frame byte.
Step4: End.
Table 1 Number corresponds to each Litter
Litter Number Litter Number Litter Number Litter Number
A 00 H 07 O 14 V 21
B 01 I 08 P 15 W 22
C 02 J 09 Q 16 X 23
D 03 K 10 R 17 Y 24
E 04 L 11 S 18 Z 25
F 05 M 12 T 19 - 26
G 06 N 13 U 20

4. International Journal of Computer Engineering and Technology (IJCET), ISSN 0976-6367(Print),
ISSN 0976 – 6375(Online) Volume 4, Issue 4, July-August (2013), © IAEME
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Figure 1: Schematic block diagram for the embedding process
3.2 EXTRACTION PHASE
The input to the extraction phase is the stego video, and RSA privet key of the receiver, while
the output is the hidden secret message. The block diagram of the extraction processes is shown in
Figure (2) and the algorithm consists of the following steps described below:
Step1: Stego video preprocessing: split the stego video into a sequence of frames, each stego video
frame dimension is H ×W Pixels. For each randomly selected frame convert into grayscale frame,
then apply edge detection using (Prewitt and Canny) algorithm. Apply cubic spline interpolation
algorithm over the generated edge. Find control points to the generated cubic spline curve.
Step2: Extract processing: Extract the stegovideo frame pixels in which the interplant curve pass
by. While the extracted stego video frame pixels are not empty, get the first bit of each byte. End of
while. End of frames.
Step3: Decrypted message processing: Combined each seven bits of the extracted bits into digital
number. Apply RSAdecryption Algorithm as in [9].Convert the result digit of size two into character
using Table (1). The result is the secret message.
Step4: END.
Stego Video
Secret
Message
Public Key
RSA
Encryption
Encrypted
Message
Cover Video
Split into
Frames
Frame
Canny Edge
Detection
RGB to
Grayscale
Prewitt Edge
Detection
Cubic Spline
Control
FFT
LSB
IFFT

5. International Journal of Computer Engineering and Technology (IJCET), ISSN 0976-6367(Print),
ISSN 0976 – 6375(Online) Volume 4, Issue 4, July-August (2013), © IAEME
244
Figure 2: Schematic block diagram for the extracting process
3. PERFORMANCE EVALUATION EXPERIMENTAL RESULTS
Steganography depends on the availability of two parameters, namely; imperceptibility and
capacity. The perceptual imperceptibility of the embedded information is measured by comparing the
original video to its stego counterpart so that their visual differences, if any, can be determined.
Additionally, as an objective measure, Average Peak Signal to Noise Ratio (APSNR) between the
cover and stego video may be calculated. These parameters are given by [6]:
,……………………….……… (1)
Where and are the pixel values at row i and column j of the cover frame and stego frame
respectively.
The Average Mean Square Error (AMSE) is given by:
,……………..………………………….……. (2)
Where N is the number of frames for each video
Secret Message
Cubic Spline Control Points
LSB Extraction RSA Decryption
RSA Secret Key
Prewitt Edge Detection
RGB to Grayscale
Canny Edge Detection
Frame
Split Frames
Stego Video

6. International Journal of Computer Engineering and Technology (IJCET), ISSN 0976-6367(Print),
ISSN 0976 – 6375(Online) Volume 4, Issue 4, July-August (2013), © IAEME
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The Peak Signal to Noise Ratio (PSNR) defined as [6]:
,………………………...………………… (3)
Where L is the peak signal level (L = 255 for 8-bit gray scale frames).
The Average Peak Signal to Noise Ratio (APSNR) is given by:
,…………………...……………………….. (4)
Where N is the number of frames for each video
The maximum capacity of cover video file is given by[6]:
,…………………...…………………… (5)
The proposed algorithm has been implemented using Matlab, and Visual Basic, as shown in
Figure (3).For all tests contained in this paper, we used N = 256. The experiments were conducted on
4 Video to test the robustness of the proposed algorithm by imperceptibility. The Experimental
results show high imperceptibility where there is no noticeable difference between the stego video
and the original.
Figure 3 the proposed method implementation

7. International Journal of Computer Engineering and Technology (IJCET), ISSN 0976-6367(Print),
ISSN 0976 – 6375(Online) Volume 4, Issue 4, July-August (2013), © IAEME
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Table (2) shows the calculate AMSE, and APSNR value between the original video and stego
video for applying the proposed method to four test video.
Table 2 AMSE and APSNR
Covervideo
Resolution
(W×H)
Frame
/sec.
No.of
frames
Size(MB)
Average
PSNR
Average
MSE
Video 1 288×352 15 167 48.4 71.61 0.31
Video 2 288×352 15 190 55.1 73.52 0.32
Video 3 288×352 15 190 55.1 72.29 0.29
Video 4 288×352 15 189 55.1 72.30 0.36
In all experiments, the APSNR is greater than 72dB and AMSE is below 0.30.
Therefore experimental results show that the proposed method is effective. It maintains the quality of
the video and no variation between the cover data and stego data that can be detected by the human
vision system.
4. CONCLUSIONS AND FUTURE WORK
We proposed a method to hide secret message inside the Video, in frequency domain and
without the need to have the original Video at the extraction phase. The sender encrypts the secret
message by the RSA public key of the recipient and then embedded it using LSB of the pixels that
located by the edge method (prewitt and canny) over the original video frame specified by the
control points of cubic spline interpolation method, after conversion it into DFT and then IDFT
applied to the real part of DFT, where the secret message is embedded using LSB insertion
method. This process is repeated for each selected frame of the cover video. The receiver extract
the LSB of the pixels that located by the edge method (prewitt, and canny) over the stego video
frame specified by the control points of cubic spline interpolation method. This process is repeated
for each selected frame of the stego cover video until all the embedded bits are extracted. The
receiver revel the encrypted secret message with his RSA secret key .The proposed method relies
on a set of parameters of secrecy, making it more resistant to attack by intruders. From these
parameters: RSA secret key, which is used to decrypt the encrypted secret message, the number of
control points which is used for each cubic spline that correspond to each edge in each used frame.
These parameters must be known to intruders to extract secret message from the stego video file
even he know the proposed algorithm. Future directions are: the use of other ways to find the edges,
the use of other interpolation methods, or the adoption of other places for embedding, the use of
wavelet transform.

8. International Journal of Computer Engineering and Technology (IJCET), ISSN 0976-6367(Print),
ISSN 0976 – 6375(Online) Volume 4, Issue 4, July-August (2013), © IAEME
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