1. Fifth International Conference on Information
and Communications Security ICICS 2003
Huhehaote City, Inner-Mongolia, China, October, 2003
A DWT-based Digital Video Watermarking Scheme with Error Correcting Code
Pat P. W. Chan and Michael R. LYU
Computer Science and Engineering Department
The Chinese University of Hong Kong

2. Outline Introduction New Video Watermarking Algorithm
Experimental Results
Future Direction
Conclusion

3. Watermarking Algorithm
Introduction
Watermarking is a concept of embedding a special pattern, watermark, into a document.
Watermarking is a key process for the protection of copyright ownership of electronic data.
In this presentation, we will focus on the video watermarking scheme.
Watermarking Algorithm
Watermarked
Image Ì
Stego-Image I
Watermark W
Secret / public key K

4. Introduction Video watermarking is challenging
Video watermarking introduces some issues not present in image watermarking.
Due to large amounts of data and inherent redundancy between frames, video signals are highly susceptible to pirate attacks, including frame averaging, frame dropping, frame swapping, statistical analysis, etc.
However, the currently proposed algorithms do not solve these problems effectively.
Existing techniques are not aware of the usefulness of the audio channel in a video.

5. Introduction
A new scheme for robust blind digital video watermarking with error correcting code will be introduced.
The features of the video watermarking algorithm are:
Our scheme embeds different parts of a single watermark into different scenes of a video under the wavelet domain;
To increase robustness of the scheme, the watermark is refined by the error correcting code, while the correcting code is embedded as watermark in the audio channel;
Our video watermarking algorithm is robust against the attacks of frame dropping, averaging and statistical analysis;
It allows blind retrieval of embedded watermark which does not need the original video;
The watermark is perceptually invisible.
To tackle these problems. we’ve proposed a new scheme for robust blind digital video watermarking with error correcting code.

6. Watermarking Scheme Overview

7. Video Preprocess: DWT & Scene Change Detection
Video frames are transformed to wavelet domain.
Perform scene change detection.
Each scene is embedded with the same watermark, so it can prevent attackers from removing the watermark by frame dropping.
Different watermarks used for successive different scene can prevent attackers from colluding with frames from completely different scenes.
Mark with m1
Mark with m3
Mark with m7
Mark with m0
Scene change occur

8. Watermark Preprocess
Scale the watermark to a particular size with the following equations
2n ≦m , n>0
p + q = n , p and q > 0
Size of image = 64˙2p X 64˙2q
Divide the image into 2n small images with size 64 X 64
m -- # of scene change of the video
Different frames using different watermarks can make the watermarks resistant to attacks by frame averaging
Hard to reconstruct the watermark without knowledge
m=10, n=3, p=1, q=2

9. Watermark Preprocess Encrypted watermark m’0 Original watermark
Preprocessed watermark m0-m7

10. Video Watermark Embedding
Exchange C[i] with max(C[i], C[i+1], C[i+2], C[i+3], C[i+4]) while W[j] = 1
Exchange C[i] with min(C[i], C[i+1], C[i+2], C[i+3], C[i+4]) while W[j] = 0
LL, HH coefficients are not watermarked

11. Audio Watermark
Error correcting code is extracted from the watermark image
Embedded in audio channel as an audio watermark
This watermark can provided the error correction and detection capability for the video watermark
Average

12. Audio Watermark Embedding
Spread-Spectrum Watermarking
Modulated Complex Lapped Transform (MCLT)

13. Watermarked Frame & Wave
Original video frame and wave
Watermarked video frame and wave

14. Watermark Detection Video is split into video stream and audio stream.
Watermarks are extracted separately by audio watermark extraction and video watermark extraction.
Then the extracted watermark undergoes refining process

15. Video Watermark Detection
if WC[i] > median(WC[i], WC[i+1],WC[i+2], WC[i+3], WC[i+4]) W[j] = 1 else W[j] = 0
Original video frame
Watermarked video frame
Extracted Watermark
Recovered Watermark

16. Watermark Refining
Error correcting codes are extracted from the audio stream
The video watermark extracted is refined by this information with the following equation
k = kth block of the average image
i = x-coordinate of video watermark
j = y-coordinate of video watermark
T = Threshold that the pixel need to correct
P: Q = the ratio of importance of extracted watermark to the average

17. Experimental Setup
VirtualDub -- a video capture/processing utility (
A video clip with 1526 frames of size 352 X 288
Experiments:
Experiment with Frame Dropping
Experiment with Frame Averaging and Statistical Analysis
Experiment with Lossy Compression
Experiment with Cropping Watermarked Frame
Measurement:

18. Experiment with Frame Dropping
As a video contains a large amount of redundancies between frames, it may suffer attacks by frame dropping.
From the experiment, we found that our scheme achieves better performance than the DWT-based scheme without scene-based watermarks.

19. Experiment with Frame Averaging and Statistical Analysis
Frame averaging and statistical analysis is another common attack to the video watermark.
When attackers collect a number of watermarked frames, they can estimate the watermark by statistical averaging and remove it from the watermarked video
Scenario of statistical averaging attack

20. Experiment with Frame Averaging and Statistical Analysis
The watermarked video is statistically analyzed by colluding a number of video frames and the watermarks are extracted and NC values are obtained.
It is found that the proposed scheme can resist to statistical averaging quite well.

21. Experiment with Lossy Compression
The performance of the scheme is significantly improved by combining with audio watermark, especially when the quality factor of MPEG is low.
When the quality factor of MPEG is low, the error of the extracted watermark is increased and the watermark is damaged significantly.
As the error correcting code is provided from the audio watermark, it can survive the attack by lossy compression which is applied to the video channel.

22. Experiment with Cropping Watermarked Frame
DWT inherits many advantages in resisting the attacks on the watermarked frames. It achieves perceptual invisibility and attacks by image processing techniques.
Cropping is one of the most common attack to video watermark.

23. Conclusion & Future Direction
Video watermarking is needed since copyright protection is essential.
Video watermarking is different from image watermarking.
A DWT-based Digital Video Watermarking Scheme with Error Correcting Code is proposed.
Use visual-audio watermark to increase the robustness of the scheme.
Increase robustness of the scheme by improving the way to embed the watermark.
Use better error correction coding.
Make use of the information from the video, such as time information to increase the robustness of the watermark.

24. Q & A