Digital watermarking allows users to embed invisible patterns or data into digital media like images, audio, and video without degrading quality. It works by modifying the media's content data rather than metadata. Watermarking is used to protect copyright ownership of electronic data by making the embedded information inseparable and able to survive various processing without changing the file size. There are different types of watermarks classified by human perception (invisible, visible), robustness (fragile, semi-fragile, robust), and document type (text, image, audio, video). Frequency domain techniques like DCT are often used for video watermarking. The purpose is for copyright protection, fingerprinting, copy protection, and authentication.

1. By: Vladimir Novikov

2. Digital Watermarking?
 Allows users to embed SPECIAL PATTERN or
SOME DATA into digital contents without
changing its perceptual quality.
 When data is embedded, it is not written at
HEADER PART but embedded directly into
digital media itself by changing media contents
data
 Watermarking is a key process for the
PROTECTION of copyright ownership of
electronic data.

3. Features of Watermarking
 Invisible/Inaudible
 Information is embedded without digital content
degradation, because of the level of embedding
operation is too small for human to notice the
change.
 Inseparable
 The embedded information can survive after some
processing, compression and format transformation.
 Unchanging data file size
 Data size of the media is not changed before and
after embedding operation because information is
embedded directly into the media.

4. How It Works

5. CLASSIFICATION OF
WATERMARK
 According to Human Perception
 Invisible
 Visible
 According to Robustness
 Fragile
 Semi fragile
 Robust
 According to types of Document
 Text
 Image
 Audio
 Video

6. CLASSIFICATION BY
“HUMAN PERCEPTION”

7. Visible Watermark
 Logo or seal of the organization which holds
the rights to the primary image, it allows the
primary image to be viewed, but still visible it
clearly as the property of the owning
organization.
 Overlay the watermark in such a way that
makes it difficult to remove, if the goal of
indicating property rights is to be achieved.

8. Visible Watermark
Watermark
Image with watermark

9. Invisible Watermark
 Embedding level is too small to notice
 Can be retrieved by extraction software
 Applications:
 Authentication
 Copyrighting
 Etc…

10. Invisible Watermark

11. CLASSIFICATION BY
“ROBUSTNESS”

12. Fragile/Semi Fragile/Robust
 A watermark is called fragile if it fails to be
detected after the slightest modification.
 A watermark is called semi-fragile if it
resists beginning transformations but fails
detection after malignant transformations.
 A watermark is called robust if it resists a
designated class of transformations.

13. CLASSIFICATION BY
“DOCUMENT”

14. Text/Image/Audio watermarking
 Text/Image/Audio watermarking refers to
embedding watermarks in an
text/image/audio in order to protect the
image from illegal copying and identify
manipulation.

15. Video Watermarking
Algorithm for video watermarking
 DFT
 DCT
 DWT
 Watermarking in I-frame.
Video watermarking refers to embedding
watermarks in a video sequence in order to protect
the video from illegal copying and identify
manipulation

16. Discrete Cosine Transformation
 DCT convert images from spatial-domain to frequency-
domain to decorrelate pixels
 The discrete cosine transform (DCT) helps to separate
the image into parts of differing importance (with
respect to the image's visual quality). The DCT is
similar to the discrete Fourier transform
 Remember that JPEG breaks an image into 8x8 units
So for DCT n = 8
For example:
256 gray-scale image each pixel is stored as a value
between 0 – 255
0 = black pixel
255 = white pixel
Value between are shades of gray

17. Wave Transforms
Frequency

18. DCT: One Dimensional
where
 






 



1
0
)
(
2
)
1
2
(
cos
2
)
( )
(
n
i
i
f
n
u
i
p
n
u
F i

n = total no. of data item
p = pixel
F = coefficients
f(i)= is the intensity of the i th pixel
The general equation for a 1D (n data items) DCT is
defined by the following equation:

19. DCT: 2D
)
,
(
2
)
1
2
(
cos
2
)
1
2
(
cos
2
2
)
,
(
1
0
1
0
)
(
)
(
j
i
f
m
v
j
n
u
i
p
p
m
n
v
u
F
n
i
m
j
j
i





 






 
 






•The input image is of size n by m;
•f(i,j) is the intensity of the pixel in row i and column j;
•F(u,v) is the DCT coefficient in row k1 and column k2 of
the DCT matrix.
The general equation for a 2D (N by M image) DCT is
defined by the following equation:

20. Watermarking in Video(DCT)

21. Frequency Domain
 Watermarking signal to embed
 Host signal
 Frequency components(using DCT)
 Embedding
 Extraction
N
v
v
v
V ,...,
, 1
0

N
x
x
x
X ,...,
, 1
0

N
f
f
f
F ,...,
, 1
0

i
i
i x
f
f 


i
i
i f
f
x 


i
f = watermared singal

22. Purpose of Watermarking
 Copyright Protection
 Fingerprinting
 Copy Protection
 Broadcasting Monitoring
 Data Authentication