Fidelity-Controlled Robustness Enhancement of Blind Watermarking Schemes Using Evolutionary Computational Techniques
Designing optimal watermarking schemes is inherently an interesting and difficult problem since the three most important performance requirements of digital watermarking – fidelity, robustness and watermark capacity – are conflicting with each other. Nowadays, most watermarking schemes hide the watermark information in a heuristic manner, that is, watermarks are often embedded according to predefined rules and empirical parameter settings. Therefore, the performance of digital watermarking can only be passively decided and evaluated, rather than being actively adopted as additional clues helpful to achieve better performance in embedding modules. In this paper, watermark embedding is simulated as an optimization procedure in which optimal embedded results are obtained by using important evolutionary computation techniques – the genetic algorithms. Under the condition that fixed amount of watermark bits are hidden, in this work, the minimal fidelity requirement of embedded content can be specified by users in advance and guaranteed throughout the embedding procedure. Furthermore, concrete measures of the robustness against certain attacks are treated as the objective functions that guide the optimizing procedure. In other words, a blind watermarking scheme with application-specific data capacity, guaranteed fidelity, and theoretically optimal robustness against certain types of attacks is proposed. Experimental results clearly show that the proposed scheme possesses great performance improvements over the original one. More importantly, the proposed enhancing approach has many desired architectural characteristics, such as blind detection, asymmetric embedding/detection overheads, as well as embedding and detection in different domains.
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