A New Approach to Image Steganography using Bit Plane ...

D. Saritha et al., International Journal of Research in Engineering, IT and Social Science, ISSN 2250-0588, Impact

Factor: 6.565, Volume 09, Special Issue 1, May 2019, Page 146-151

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A New Approach to Image Steganography using

Bit Plane Slicing and Convolution

D. SARITHA1, A. AJANTHA

2, A. MALLIKARJUN REDDY

3, J. NAVEEN

4, CH. ANJUSHA

5

1UG Scholar, Dept. of ECE, Narayana Engineering College, GUDUR, AP, India,




5Associate Professor, Dept. of ECE, Narayana Engineering College, GUDUR, AP, India,

Abstract-- The novel algorithm is based on bit plane

slicing technique. The basic idea is to divide the

secret image into four parts and these four parts of

the secret image are then embedded into four

different cover images using a secret key to prevent

image intrusions or hacking. The four stego images

are then transmitted to the intended receiver. The

receiver receives four stego images which contains

four parts of the secret image. These four parts of

the image are then extracted using an algorithm and

a secret key which again works on bit operations.

The extracted images are then restructured to

reconstruct the original secret image. This algorithm

offers very low distortion between the actual image

and the reconstructed image with cross correlation

between two images being in the range 0.91 – 0.99

thus indicating very high image retrieval and at the

same time a secured transmission algorithm for

critical secret image transmission. The parameters

used to test the robustness of the algorithm are Mean

Square Error (MSE), Peak Signal to Noise Ratio

(PSNR) and Normalized Cross-Correlation.

Index Terms- Steganography, Stego image, Bit

Plane Slicing, Convolution, MSE, PSNR, Normalized

Cross Correlation.

I. INTRODUCTION

owadays most of the internet users need to store,

send or receive data. The common way to do this is

to transform the data into some unknown form.

The resulting data can be understood only by those who

know how to return it to its original form. This way of

protecting information is known as encryption. The

major drawback of encryption is the existence of data is

not hidden.

A. Steganography

Steganography[1]

is the art and science of invisible

communication. Steganography is a Greek word which

literally means “covered writing”. The word

steganography is divided into two words Steganos and

graphein, where Steganos means “hidden” or “covered”

and graphein means “to write”[2]

.

Steganography is the art and science of

communicating in a way which hides the existence of

the communication. Steganographic technologies are a

very important part of the future of Internet security and

privacy on open systems such as the Internet[3]

.

The main goal of steganography is to transmit the secret

image securely so that the third party cannot understand

the transmission of secret image.

Basic key words in steganography are

Payload: The information which is to be hidden.

Carrier File: The media where payload has to be

hidden.

Stego-Medium: The medium in which the

information is hidden.

Steganalysis: The process of detecting hidden

information inside of a file.

The message hidden in the selected media is transmitted

to recipient[4]

. At receiver end, reverse process is

implemented to recover the original message.

The basic steganography system[1]

scenario is as shown

below:

N





Figure1: Steganography system scenario.

1. Steganography Types

There are basically three types of steganography

protocols used[3]

. They are

P

ure steganography

S

ecret key steganography

P

ublic key steganography

Pure steganography: In pure steganography system, the

secret key is not exchanged between the transmitter and

the receiver. This method of steganography is least

secured.

Secret key steganography: In secret key steganography

the secret key is exchanged between transmitter and

receiver prior to communication. The major advantage

of secret key steganography is that the parties who

know the secret key can extract the secret message.

Public key steganography: The Public Key

Steganography uses a public key and a private key to

secure the communication between the parties wanting

to communicate secretly. The sender uses the public key

during the embedding process and the private key,

which has a relationship with the public key, can extract

the secret message. Public key steganography provides

multiple levels of security.

B. Steganography verses cryptography

Both steganography and cryptography are closely

related. Cryptography scrambles the secret image that is

the secret image is transferred into an unknown format

which is not understandable[1]

. Whereas on the other

hand steganography hides the secret image in another

media so that there is no knowledge of existence of

secret image.

C. Data hiding

Data hiding is defined as a set of processes used to

embed secret data into various forms of media such as

text, audio, or image with minimum amount of

degradation to the original data[2]

.

1. Applications of Data Hiding

Important applications of data hiding in digital media

can be considered in terms of proof of the copyright and

content integrity assurance. Therefore, the secret data

should be kept hidden in the host image, even if there is

a possibility that the image is subjected to some

manipulation techniques[2]

. Another application is to

hide more data in a featured location.

2. Goals of Data Hiding

a) The secret image should be directly embedded into

the cover image.

b) The embedded data should be protected from

channel noise, cropping, filtering, lossy

compression etc.

D. Bit plane slicing

Image enhancement is the method of enhancing the

low contrast image. But the drawback of this method is

that all the pixels in the image are brightened totally and

this may not be suitable for some applications. So to

overcome this, Bit-Plane Slicing method[6]

is used. Bit-

Plane Slicing is a technique in which the image is sliced

at different planes.

The bit plane image corresponding to the plane of the

most significant bit (MSB) has the maximum

contribution to the total image and forms the majority of

the visually significant image data and planes

corresponding to other lower bit positions contribute

only the subtle details of the image.

It ranges from Bit level 0 which is the least significant

bit (LSB) to Bit level 7 which is the most significant bit

(MSB). The input to this method is an 8-bit per pixel

image. This is a very important method in Image

Processing[5]

.

Figure2: Bit Plane Slicing.

The advantage of this method is that it gives the relative

importance of each bit of the image. It also highlights

the contribution made by specific bits.

II. REQUIREMENTS

1. The cover image should be exactly half that of the

secret image that is if the secret image is of size

1024×768 then the size of the cover image should be

512×384.

2. To achieve better maximum PSNR and normalized

cross-correlation between the original secret image

and the extracted secret image.

III.

III. PROPOSED ALGORITHM

In this algorithm the secret image is divided into

four parts and these four parts of the secret image are

then embedded into four different cover images using a

secret key. The processed four images (stego images)

are then transmitted to the intended receiver. The

receiver receives four stego images which contains four

parts of the secret image. These four parts of the image





are then extracted using an algorithm and a secret key

which works on bit operations. The extracted images are

then restructured to obtain the secret image.

A. Embedding process

The embedding process is as follows:

1. Select the secret image.

2. Divide the secret image into four parts.

3. Select four cover images. Cover images should be

exactly 1/2

that of the secret image.

a. Provide the secret key '4321' to execute the

program

4. Convolving the upper left part of the secret image

with that of the first cover image using Bit Plane

technique.

5. Write the convolution of upper left part with that of

cover image in a .bmp file to avoid any sort of loss in

lower bits.

6. Convolving the upper right part of secret image with

that of the second cover image using Bit Plane

technique.

7. Write the convolution of the upper right with that of

cover image in a .bmp file to avoid any sort of loss in

lower bits.

8. Convolving the lower left part of secret image with

that of the third cover image using Bit Plane

technique.

9. Write the convolution of the lower left part with that

of cover image in a .bmp file to avoid any sort of

loss in lower bits.

10. Convolving the lower right part of secret image with

that of the fourth cover image using Bit Plane

technique

11. Write the convolution of the lower right part with

that of cover image in a .bmp file to avoid any sort of

loss in lower bits.

12. End of embedding process.

1. Extracting process

The extracting process is as follows:

1. Select the four stego images obtained from the

embedding process.

2. P

rovide the secret key '1234' to perform the extraction

process.

3. T

he four stego images undergoes blind deconvolution

where the four parts of the secret image are

retrieved.

4. T

he four parts retrieved after deconvolution are

restructured to obtain the actual secret image.

B. RESULTS

Selecting the secret image as shown below.

Figure 3: Selecting the secret Image.

The selected secret image will be displayed as shown

below.

Figure 4: Selected secret Image.

The selected secret image is cropped into four parts as

shown below.





Figure 5: Four parts of secret Image

The four cover images are selected as shown below.

Figure 6: Selecting cover images.

The selected four cover images are as shown below.

Figure 7: Selected four cover images.

Providing the secret key to embed the secret image parts

into selected cover images as shown below.

Figure 8: Providing the secret key for embedding process.

The four different stego images obtained after

embedding the four secret image parts in four cover

images are shown below.

Figure 9: Four stego images.

The four different stego images received at the receiver

are as shown below.





Figure 10: Four received stego images.

Provide the secret key to extract the secret image parts

from the four different stego images as shown below.

Figure 11: Providing the secret key for extraction process.

The secret image parts extracted from the four different

stego images are as shown below.

Figure 12: Extracted secret image parts.

The extracted secret image parts are restructured to form

the original secret image as shown below.

Figure 13: Extracted secret image.

The obtained quality analysis parameters between the

original secret image and the retrieved secret image are

as shown below.

Figure 14: Quality analysis parameters.

C. SOFTWARE TOOL

Matlab R2013a

D. CONCLUSION

The proposed image steganography method gives

better security as the secret image is divided in 4 parts.

Hence to retrieve the secret image the receiver has to

use four stego images, thus if anyone tries to steal some

of the data they won’t be able to retrieve the image

unless they have all the four images. Further the secret

key used in the algorithm gives additional security in

the process hence eliminating any unauthorized viewing

of the message. The hidden image and the retrieved

image has a normalized cross correlation of 0.9306 thus

indicating a retrieval of 93.06% of the secret image

which indicates very high and efficient performance of





the algorithm. The algorithm uses very less memory for

computation and at the same time gives a good result in

very short time, thus indicating sensitivity and memory

efficient algorithm.

REFERENCES

[1] Arvind Kumar, Km. Pooja, “Steganography- A

Data Hiding Technique”, International Journal of

Computer Applications (0975 – 8887), Volume 9–

No.7, November 2010.

[2] Fahim Irfan Alam, Fateha Khanam Bappee, Farid

Uddin Ahmed Khondker, “An Investigation into

Encrypted Message Hiding Through Images Using

LSB”, International Journal of Engineering Science

and Technology (IJEST), Vol. 3 No. 2 Feb 2011.

[3] Jammi Ashok, Y.Raju, S.Munishankaraiah,

K.Srinivas, “Steganography: An Overview”,

International Journal of Engineering Science and

Technology, Vol. 2(10), 2010, 5985-5992.

[4] Sujay Narayana, Gaurav Prasad, “Two New

Approaches For Secured Image Steganography

Using Cryptographic Techniques And Type

Conversions, An International Journal(SIPIJ) Vol.1,

No.2, December 2010.

[5]

http://bitplaneslicing.wordpress.com/2012/02/23/b

it-plane-slicing/

[6] Dr.M.Mohammed Sathik, N.Ravia Shabnam

Parveen, “Feature Extraction On Colored X-Ray

Images By Bitplane Slicing Technique”,

International Journal of Engineering Science and

Technology, Vol. 2(7), 2010, 2820-2824.

[7] R. EI Safy, H. H. Zayed, A. EI Dessouki, “An

Adaptive Steganographic Technique Based on

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8/09, 2009IEEE.

[8] S. Jayasudha, “Integer Wavelet Transform based

Steganographic Method using OPA Algorithm”,

International Conference on Computing and

Control Engineering (ICCCE 2012), 12 & 13

April, 2012.

[9] Wien Hong and Tung-Shou Chen, “A Novel Data

Embedding Method Using Adaptive Pixel Pair

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Forensics And Security, VOL. 7, NO. 1, February

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http://bitplaneslicing.wordpress.com/2012/02/23/bit-plane-slicing/



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