Image steganography is the art of hiding information within digital images. The document discusses various techniques for image steganography including LSB (least significant bit) and DCT (discrete cosine transform). LSB is a simple spatial domain technique that replaces the least significant bits of image pixels with bits of a secret message. DCT operates in the frequency domain by transforming image blocks and hiding data in the mid-frequency DCT coefficients. The document compares the advantages and disadvantages of these techniques, and discusses their applications for hiding private information or digital watermarking. Metrics for analyzing steganography systems like bit error rate, mean square error, and peak signal to noise ratio are also introduced.

1. IMAGE
STEGANOGRAPHY
Guided By:
Prof. Nikunj Gamit
Prepared By:
Nidhi Papaiyawala
201203100810041
(6th IT)

2. Content
 Definition of image steganography
 Advantages
 Limitations
 Application
 Block diagram of steganography
 Different techniques
 Introduction of LSB technique
 Merits and Demerits of LSB
 Introduction of DCT technique
 Application
 Error analysis
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3. Image steganography
 Definition:
Steganography is the art of “concealed
writing” and it refers to techniques that hide
information inside objects known as “Cover
Objects”.
2

4. Advantages of steganography
 The secret message does not attract attention to
itself as an object of scrutiny.
 steganography is concerned with concealing a
secret message is being sent, as well as
concealing the contents of the message.
 Difficult to detect. Only receiver can detect.
 Provides better security for data sharing.
3

5. Limitations
 The confidentiality of information is maintained
by the algorithms, and if algorithms are known
then this technique is of no use.
 Password leakage may occur and it leads to the
unauthorized access of data.
4

6. Application
 several information sources like our private
banking information, some military secrets, can
be stored in a cover source.
 Steganography is used by some modern printers
and color laser printers.
 Steganography can be used for digital
watermarking.
5

7. Basic Block diagram
Embedding information:
6
Embedding
Process
Stego-Key
Embedded
message
Cover
Image
Stego
Image

8. (cont.)
Extracting information:
7
Extracting
Process
Stego-Key
Cover
Image
Stego
Image
Embedded
message

9. Different Techniques[1]
There are two categories:
1)Spatial Domain:
which mainly includes LSB(Least
Significant Bit)
2)Frequency Domain:
which includes DCT(Discrete cosine
transform) and Wavelet Transform.
8

10. Least Significant Bit
 Simple approach to embedding information in
a cover image.
 It operates on principle that the human eye can
not differentiate between two shade separated by
only one bit.
Algorithm to embed the message:[1]
 Read the cover image and text message which is
to be hidden in the cover image.
 Convert the color image into grey image.
9

11. (cont.)
 Convert text message in binary.
 Calculate the LSB of each pixel of cover image.
 Replace LSB of cover image with each bit of
secret message one by one.
 Write stego image.
10

12. Algorithm to extracting message
 Read the stego image.
 Calculate the LSB of each pixel of stego image.
 Extract the bits and covert each 8 bit in to
character.
11

13. Result of LSB
12
Cover image Stego image

14.  Merits
1) Simple to
implement.
2) High payload
capacity.
3) Low complexity.
 Demerits:
1) Vulnerable
corruption.
2) Vulnerable to
detection.
13

15. DCT(Discrete cosine transform)
 The DCT transforms a signal or image from the
spatial domain to the frequency domain.
 Grouping the pixels into 8 × 8 pixel blocks and
transforming the pixel blocks into 64 DCT.
 DCT allows an image to be broken up into
different frequency bands namely the high,
middle and low frequency bands
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16. Process of DCT based image
Steganography are as follow:[2]
Embedding information:
 Load cover image and secret image.
 Divide the cover image in to 8x8 blocks of
pixels.
 Transform the cover image from spatial domain
to frequency using two dimensional DCT .
 Quantize the DCT coefficients by dividing using
factor in to the rounded value. 15

17. (cont.)
 Encrypt the secret image using RSA algorithm.
 Divide the encrypted image in to 8x8 blocks.
 Embed this data in the mid DCT coefficients of
cover image.
 Apply two dimensional inverse DCT to view it
in the spatial domain.
16

18. Block Diagram of DCT[2]
secret
message
17
Encryptio
n
Embeddi
ng
2D DCT
on each
block
8*8 block
preparatio
n
Cover
image
2D IDCT
on each
block
Stego
Embedding information:

19. Extracting information
 Read the Stego image.
 Divide the stego image in to 8x8 blocks of
pixels.
 Transform the stego image from spatial to
frequency domain by applying two dimensional
DCT on each block
 Quantize the DCT coefficients in to the rounded
value.
18

20. (cont.)
 Extract the encrypted image values from mid-
frequency coefficients.
 Decrypt the values using RSA algorithm.
 Apply two dimensional inverse DCT to view the
extracted image in the spatial domain.
19

21. Extracting information[2]
20
Stego
image
8*8 block
preparatio
n
2D DCT
on each
block
Extraction
2D IDCT
on each
block
Decryptio
n
Extracted
image

22. Result of DCT
21
Cover Image Secrete Image

23. Output at the receiver side
Cover Image Stego Image
22

24. Advantages
 Energy compaction.
 High compression ratio,
 Small bit error rate
 Good information integration ability.
23

25. Application
 It is often used in image processing, especially
for lossy compression, because it has a strong
"energy compaction" property.
24

26. Error Analysis [2]
(I)Bit Error Rate(BER):
 For the successful recovery of the hidden
information the communication channel must be
ideal.
 for the real communication channel, there will
be error while retrieving hidden information and
this is measured by BER.
all pixel
BER= 1 ∑ |image cov -image steg |
|image cov| i=0
25

27. (cont.)
(II)Mean Square Error:
 It is defined as the square of error between cover
image and stego image.
 The distortion in the image can be measured
using MSE and is calculated using Equation
n
MSE = 1 ∑ (cov-steg)2
n i=0
26

28. (cont.)
(III)Peak Signal to Noise Ratio (PSNR)
 It is the measure of quality of the image by
comparing the cover image with the stego
image, i.e. Difference between the cover and
Stego image is calculated using Equation.
PSNR = 10log10 2552/MSE
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29. Conclusion.
 Steganography is the art and science of writing
hidden message that no one apart from the
sender and receiver, suspect the existence of the
message.
 DCT-Steganography is based on encryption. To
provide high security Steganography and
cryptography are combined together. This
technique encrypts secret information before
embedding it in the image.
 Larger PSNR indicates the higher the image
quality . a smaller PSNR means there is huge
distortion between the cover-image and the
stego image.
28

30. References
 Anil k Jain, “Fundamentals of digital image
processing", University of california-
davis,prentice hall.
 Proceeding of the 2006 International conference
on “Intelligent information hiding and
multimedia signal processing 2006 IEEE.
 K.B.Raja', C.R.Chowdary2, Venugopal K R3,
L.M.Patnaik , A Secure Image Steganography
using LSB, DCT and Compression Techniques
on Raw Images,2005 IEEE 29

31. THANK YOU
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