1. Independent component analysis in the blind watermarking of digital images
Authors: J.J. Murillo-Fuentes
Source: Science Direct Neurocomputing 70 (2007)
Speaker: Wei Chun, Lin

2. Outline Introduction ICA in image process
ICA in watermarking of digital images
A general ICA-based watermarking algorithm
A practical RW algorithm
Experimental results
Conclusions

3. Introduction
Image watermarking allows the protection of copyrighted data by ownership verification, preventing unauthorized distributions.
Direct embedding in the spatial domain is desirable for low- complexity requirements. However, it may be easily attacked.
Other techniques based on transformed domains are usually more robust.
The basic idea of ICA RW is to project the image into independent components, the transform coefficients, to embed the watermark into them.

4. ICA in image process
There are two common applications of ICA to image processing.
1. l linear mixtures of l images.
2. only one image is involved.

5. ICA in image process

6. ICA in image process

7. ICA in watermarking of digital images
The cover (or original) image I and the watermark W are reshaped into vectors, xIt and xWt , and then the watermark is inserted into the cover image by mixing them.

8. A general ICA-based watermarking algorithm
Embedding

9. A general ICA-based watermarking algorithm

10. A general ICA-based watermarking algorithm
Detection

11. A general ICA-based watermarking algorithm

12. Experimental result

13. Experimental result

14. Conclusion The robustness of the method rests on two main ideas.
1. the ICA projection used is a key of the method as it is needed to completely remove the watermark.
2. the statistical and spectral characteristics of the independent components are close to that of the spread sequence.