Title of Thesis

Intelligent Perceptual Shaping of a Digital Watermark

Author(s)

Asifullah Khan

Abstract
Embedding of a digital watermark in a digital media is proving to be a workable solution for many of the recent problems like copyright protections and content authentication. However, the embedding of a digital watermark in a digital media is not without constraints. This requires perceptual shaping of a watermark in context of Human Visual System (HVS). The goal of this thesis is to develop a new watermarking scheme based on intelligent shaping of a digital watermark using GP. To achieve this goal, the research focuses on making efficient tradeoffs between two of the most important, but contradicting properties of a watermarking system; robustness and imperceptibility.
This thesis makes the following contributions: (1) An analysis of the importance of perceptual shaping of a watermark in making a trade off between robustness and imperceptibility is performed, (2) intelligent search technique, like GP, is used to exploit the characteristics of HVS inevolving superior perceptual shaping functions, (3) the concept of bonus fitness has been proposed to implement multi-objective fitness function, in the GP simulation. This helps in simultaneously handling the estimated robustness and imperceptibility requirements during embedding stage, and actual robustness during decoding stage, (4) we realize that perceptual shaping of a watermark is not only important for making a superior trade off, but could also be used to tailor the watermark in accordance to an anticipated attack, (5) watermarking systems are becoming more and more sophisticated, as such this thesis, using intelligent search technique like GP, points towards the solution strategy of many complex issues in watermarking that are difficult to be computed analytically. A series of empirical investigations are performed to analyze the performance of the genetically evolved perceptual shaping functions (GPSFs) using standard benchmark, which shows the effectiveness of our approach.

1.1  Research Perspective
1.2  Contributions
1.3  Structure of the thesis

2

2.1 Digital Watermarking
2.2       Perceptual Shaping of a Digital Watermark
2.3 Evolutionary Algorithms: Computational Intelligence-based Approaches
2.4 Machine Learning: The Basic Concep
2.5 Genetic Perceptual Shaping Scheme (GPSS)

3.1 Introduction
3.2 Full Frame DCT-domain Watermarking Scheme
3.3 Proposed Technique for Optimizing Perceptual Shaping of Watermark
3.4 Implementation Details
3.5 Results and Discussion
3.6 Conclusions

4.1 Introduction
4.2 Proposed Technique for Developing a GPSF
4.3 Implementation Details
4.4 Results and Discussions
4.5 Conclusions

5.1 Introduction
5.2 Proposed Technique for Developing a GPSF
5.3 Implementation Details
5.4 Results and Discussion
5.5 Conclusions

6.1 Introduction
6.2 Proposed Attack-resistant Perceptual Shaping
6.3 Implementation Details
6.4 Results and Discussion
6.5 Conclusions

7.1 Contributions: Details in reference to individual chapters
7.2 Future Work
 

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