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REVERSIBLE DATA HIDING WITH
GOOD PAYLOAD DISTORTION
ABSTRACT
 Aimed at embedding data of some secret
information in military and medical applications
were efficient data can be extracted.
 In existing system three methods were used.
1. Lossless compression.
2. Differencial expansion.
3. Histogram modification.
 Optimal value achieved reversing by using iterative
procedure.
 It proposes reversible data hiding scheme.
DESIGN OVERVIEW
Reversing dataData
Data
Embedded
data
Original Image
–Embedded
Image
Iterative procedure
Algorithm
PROPOSED IDEA
 The optimal rule of value modification under a
payload-distortion criteria is found.
 By using iterative algorithm, an optimal value
transfer matrix can be obtained.
EXISTING METHODOLOGY
 On the receiving side, the original block can be
recovered from a marked image in an inverse process.
 Payload of this method is low since each block can only
carry one bit.
 Based on this method, a robust lossless data hiding
scheme is proposed, which can be used for semi-fragile
image authentication.
PROPOSED WORK
 The Proposed system consist of a practical
reversible data hiding scheme, in which the
estimation errors of host pixels are used to
accommodate the secret data and their values are
modified according to the optimal value transfer
matrix.
 This way, a good payload-distortion performance
can be achieved.
MODULES
 Data hiding
A data-hider can also employ histogram modification
mechanism to realize reversible data hiding. The two
sub-regions on this circle is used to embed one bit
in each block. Payload of this method is low since
each block can only carry one bit.
 Optimal value transfer matrix
Iterative procedure is proposed to calculate the
optimal value transfer matrix , which will be used to
realize reversible data hiding with good payload-
distortion performance .
 Data Reversing
The secret data, as well as the auxiliary information
used for content recovery, are carried by the
differences between the original pixel-values and the
corresponding values estimated from the neighbors,
and the estimation errors are modified according to
the optimal value transfer matrix.
 Data extration and content recovery
When having an image containing embedded data,
the receiver firstly divides the image into Set Sets A
and B, and divides Sets A and B into a number of
subsets using the same manner.
SCREEN SHOTS
 Sender
 key used to extract the content
 Receiver
CONCLUSION
 By using the optimal value transfer good payload
distortion for the reversible data hiding is
achieved.
 Embedded secret data is extracted and original
content is recovered in the subset in the inverse
order to the receiver.
REFRENCES
 [1] M. Goljan, J. Fridrich, and R. Du, “Distortion-free data
embedding,” in Proc. 4th Int. Workshop on Information
Hiding, Lecture Notes in Computer Science, 2001, vol.
2137, pp. 27–41.
 [2] M. U. Celik, G. Sharma, A. M. Tekalp, and E. Saber,
“Lossless generalized- LSB data embedding,” IEEE Trans.
Image Process., vol. 14,no. 2, pp. 253–266, Feb. 2005.
 [3] J. Fridrich, M. Goljan, and R. Du, “Lossless data
embedding for all image formats,” in Proc. Security and
Watermarking of Multimedia Contents IV, Proc. SPIE,
2002, vol. 4675, pp. 572–583.
REVERSIBLE DATA HIDING WITH GOOD PAYLOAD DISTORTIONPpt 3

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REVERSIBLE DATA HIDING WITH GOOD PAYLOAD DISTORTIONPpt 3

  • 1. REVERSIBLE DATA HIDING WITH GOOD PAYLOAD DISTORTION
  • 2. ABSTRACT  Aimed at embedding data of some secret information in military and medical applications were efficient data can be extracted.  In existing system three methods were used. 1. Lossless compression. 2. Differencial expansion. 3. Histogram modification.  Optimal value achieved reversing by using iterative procedure.  It proposes reversible data hiding scheme.
  • 3. DESIGN OVERVIEW Reversing dataData Data Embedded data Original Image –Embedded Image Iterative procedure Algorithm
  • 4. PROPOSED IDEA  The optimal rule of value modification under a payload-distortion criteria is found.  By using iterative algorithm, an optimal value transfer matrix can be obtained.
  • 5. EXISTING METHODOLOGY  On the receiving side, the original block can be recovered from a marked image in an inverse process.  Payload of this method is low since each block can only carry one bit.  Based on this method, a robust lossless data hiding scheme is proposed, which can be used for semi-fragile image authentication.
  • 6. PROPOSED WORK  The Proposed system consist of a practical reversible data hiding scheme, in which the estimation errors of host pixels are used to accommodate the secret data and their values are modified according to the optimal value transfer matrix.  This way, a good payload-distortion performance can be achieved.
  • 7. MODULES  Data hiding A data-hider can also employ histogram modification mechanism to realize reversible data hiding. The two sub-regions on this circle is used to embed one bit in each block. Payload of this method is low since each block can only carry one bit.  Optimal value transfer matrix Iterative procedure is proposed to calculate the optimal value transfer matrix , which will be used to realize reversible data hiding with good payload- distortion performance .
  • 8.  Data Reversing The secret data, as well as the auxiliary information used for content recovery, are carried by the differences between the original pixel-values and the corresponding values estimated from the neighbors, and the estimation errors are modified according to the optimal value transfer matrix.  Data extration and content recovery When having an image containing embedded data, the receiver firstly divides the image into Set Sets A and B, and divides Sets A and B into a number of subsets using the same manner.
  • 10.  key used to extract the content  Receiver
  • 11. CONCLUSION  By using the optimal value transfer good payload distortion for the reversible data hiding is achieved.  Embedded secret data is extracted and original content is recovered in the subset in the inverse order to the receiver.
  • 12. REFRENCES  [1] M. Goljan, J. Fridrich, and R. Du, “Distortion-free data embedding,” in Proc. 4th Int. Workshop on Information Hiding, Lecture Notes in Computer Science, 2001, vol. 2137, pp. 27–41.  [2] M. U. Celik, G. Sharma, A. M. Tekalp, and E. Saber, “Lossless generalized- LSB data embedding,” IEEE Trans. Image Process., vol. 14,no. 2, pp. 253–266, Feb. 2005.  [3] J. Fridrich, M. Goljan, and R. Du, “Lossless data embedding for all image formats,” in Proc. Security and Watermarking of Multimedia Contents IV, Proc. SPIE, 2002, vol. 4675, pp. 572–583.