This document discusses image steganography techniques. It begins with definitions of steganography and covers advantages like concealment and security. Limitations include vulnerability if algorithms are known. Techniques covered include least significant bit (LSB) and discrete cosine transform (DCT). LSB replaces image pixel LSBs with message bits. DCT transforms images to frequency domains and embeds data in mid-frequencies. Merits of each include simplicity for LSB and energy compaction for DCT. The document provides block diagrams of embedding and extracting processes and discusses error analysis metrics.

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
1

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
14

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
27

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
30