Watermarking for Image Authentication ( Fragile Watermarking ) by jvz18720

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									 Watermarking for Image
 ( Fragile Watermarking )

Information Technologies for IPR
       Desirable Features

1. to be able to determine whether an image
   has been altered or not;
2. to be able to locate any alteration made on
   the image;

3. to be able to integrate authentication
   data with host image rather than as a
   separate data file ;
4. the embedded authentication data be
   invisible under normal viewing conditions;
5. to allow the watermarked image be
   stored in lossy-compression format.

               Block Diagram of Embedding Process

    Original                      Lookup Table
     image                           (LUT)

    Block                                            Coeffs.        Entropy
                    Quant            Embed                          Coding

                               Data to be embedded             Marked JPEG Image

(Watermark is embedded into the quantized DCT coeffs. via a look-up table)

 1. Embedding Binary Bits Via Table
A proprietary look-up table (LUT) is
generated before hand by the owner of the
image or the digital camera manufactures.
The table maps every possible value of
JPEG coeff. randomly to “1” or “0” with the
constraint that runs of “1” and “0” are
limited in length.

To embed a “1” in a coefficient, the coeff. is
unchanged if the entry of the table
corresponding to that coeff. is also a “1”.
If the entry of the table is a “0”, than the coeff.
is changed to its nearest neighboring values
for which the entry is “1”.
The embedding of a “0” is similar.

Let   νi denotes the original coeff.
      ν i′
         denotes the marked coeff.
     bi is the bit to be embedded in
  LUT(.) is the mapping by look-up table :

Then, the embedding process can be represented as :
               ⎧ν i     if LUT (ν i ) = bi
        ν i′ = ⎨
               ⎩ν i + δ if LUT (ν i ) ≠ bi , and
        δ = min{d ∈ Z : LUT (ν i + d ) = bi }

The extraction of the signature is simply by :
                  bi = LUT (ν i′ )
Where bi is the extracted bit.

Ex :       -73               1           ×           0               Embed “0” (changed)

      36 -73     8       …       0             0                                           -74
      24   5                             0                                          24
      …          original                      embedded                                           Marked
      0                          0

                                             Embed “0” (unchanged)
 24                  0               0                                     24

  LUT ‥‥‥ -75 -74 -73 -72 ‥‥ 23 24 25 ‥‥‥
      ‥‥‥ 1 0 1 1 ‥‥ 0 0 1 ‥‥‥
In this example, zeros are embedded into
two AC coefficients with values “-73” and
“24” of an 8×8 image block. The entry in
LUT for coeff-value “-73” is “1”. So to embed
a “0”, we go to its closest neighbor for which
the entry is “0”.
In this case, “-73” is changed to “-74”.
Since the entry for coeff-value “24” is “0”, it is

    2. Consideration for Minimizing

To ensure the markings are invisible :
• The run of “1” and “0” entries in the LUT is
  constrained to avoid excessive
  modification on the coeffs.
• DC coeff. in each block is not changed to
  avoid blocky effect.
• Small value coeffs are not modified to
  avoid high freq. distortion.

The above constraints make the number of
bits that can be embedded varies
significantly from block to block. Also
extraction error may occur due to image
format conversion and other causes.
For these reasons, we choose to embed
“one bit per 8×8 block” by embedding the
same bit to all embeddable coeffs in the
block and detecting that bit by “majority

1. The detection of an error in the embedded
   bit signals alteration of that block.
2. The constraint of leaving DC coeffs. and
   small valued AC coeffs unchanged makes it
   impossible to embed data in smooth blocks
   where all AC coeffs are very small and
   hence unembeddable.

    3. Choice of Embedded Data for

The authentication data we embed in an
image consists of a “visually meaningful
binary pattern” and some “content features”.
The visually meaningful pattern serves as a
quick check for alteration and location of
possible alteration.

A simple example of content feature is the
“most significant bit” of macroblock mean
Another example is the “sign” of intensity
difference between macroblocks.
The combination of these two types data is
suitable for such applications as image
authentication for “trustworthy” digital

 Image                       LUT

 block       Quant       Embed           coeff.     Entropy           Compressed
 DCT                                                coding             Marked
                  features     Binary
Test Image
(decompressed)                     LUT              Binary Pattern

 block           Quant         Extract                                visualize
 DCT                                              Embedded Features    compare

  Embedding and Extraction Procedures                                              16
      4. Smooth Region Embedding

Authentication data cannot be embedded in
smooth blocks because the AC coeffs are
This shortage can be solved by embedding
data in blocks that are not smooth but whose
location bears a “fixed relationship” to the
smooth block in question ——backup

       5. Color Image and Video

For color images, one may work in YCrCb
coordinates and use the proposed approach to
mark luminance components while leaving
chrominance components unchanged ; or one may
apply the approach to chrominance components as
well as to embed more data. One may also work in
other color coordinates, such as RGB.
 For MPEG-video, one may mark the I-frames using
the proposed scheme. The I-frame serial number
can be used as part of embedded data to detect
modification such as frame reordering and frame

[1] Yeung & Mintzer, “Invisible Watermarking for
    Image Verification”, J. of Electronic Imaging,
    pp.578-591, July 1998.
[2] P.W.Wang, “A public Key Watermark for Image
    Verification and Authentication, “ IEEE Inte’l
    conf. Image Processing, pp.455-459, Oct. 1998.
[3] Wu & Liu, “Watermarking for Image
    Authentication,” IEEE Inte’l conf. Image
    Processing, pp.437-441, Oct. 1998.
[4] Xie & Arce, “ Joint Wavelet Compression and
    Authentication Watermarking,” IEEE Inte’l conf.
    Image Processing, pp.427-431, Oct. 1998.

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