A User Attention Based
Visible Watermarking
Scheme
2003/12/15
Chen-Hsiu Huang and Ja-Ling Wu
Communication and Multimedia Laboratory, National Taiwan University,
Vis
ible
Wa
term
ark
Introduction
Digital watermarking:
the process of
embedding data into a multimedia objects so
that the embedded watermark can be
detected or extracted later.
According to human perceptivity, it can be
divided into two different types, visible and
invisible.
Visible watermark is a second transparent
pattern or image overlaid with the primary
(host) image.
Criterions about Visible Watermark
It should be
obvious to be seen
.
It should be
spread in a large or important are
a
of the image.
It should be
visible but not significantly obscur
e the details
.
It must be
difficult to remove
; it’s
more costly
and labor intensive
to remove it.
Embedding process should be
automatic, wit
Challenges for Visible Watermarks
How can we spread the embedding wat
ermark in a large or important area with
out significantly obscure the details?
If we can achieve these, how can this e
mbedding process being labor saving, t
hat is, without too much user interventio
n?
Most of the proposed schemes still treat video
data as series of pictures and apply image
watermarking schemes to each frame.
This may not suitable for video because the
most significant properties,
temporal
correlation and motion information
are not
taken into account.
With the computational attention models, we
have more objective references for choosing
the locations to insert watermarks.
The User Attention Model
Attention refers to the ability of a human to focus and
concentrate upon some visual or auditory object, by careful observing or listening.
For features in different lev
els, various saliency maps a re generated to capture user s' focus.
Once the final saliency ma
p is generated, the focus poi nt can be detected and mod els observer’s attention succ essfully.
While users pay more attention to the focus regions, t
hey usually pay less attention to other regions,
These non-focus regions are good candidates to emb
Selection of Watermark Location
For those regions far away from the focus point are
good candidates to embed watermarks.
In order to decrease the perceptual distortion, the
regions of lower intensity and higher texture are the most suitable ones.
A weighting function is
defined to measure eac h macroblock’s unsuita bility:
The one with highest u
nsuitability is selected f or embedding.
Watermark Embedding
In order not to obscure the original, we select a lumin
ance scaling coefficient φ based on background’s inte nsity and texture to scale watermark’s strength.
Shot Based Watermarking
Since the embedding process is performed on frame
level, the embedded watermark may look like another unstable moving object in the video, which is quite
annoying.
For resolving this shortage, we change our policy to
calculate the watermarking location only once in a video location only once in a video shot.
The watermark appears in the same location during
each shot and only moves when video shot-change occurs.
Results
In our scheme, owners’ rights claim is preserved with
out spoiling the video’s presentation.
The embedding process is performed once in each s
hot and will not annoy the original video due to freque ntly movements.
The watermark differs in each shot both in its location
and strength. Thus cannot be predicted in advance d ue to its content-dependent nature.
The watermarking can be done fully automatic, i.e. la
Borrowing techniques developed in the conte
nt analysis field, such as modeling of user’s at
tention, is beneficial to digital watermarking.
