Simple Collusion-Secure Fingerprinting Schemes for Images
ITCC '00 Proceedings of the The International Conference on Information Technology: Coding and Computing (ITCC'00)
An audio watermarking scheme robust against stereo attacks
Proceedings of the 2004 workshop on Multimedia and security
Audio watermark attacks: from single to profile attacks
MM&Sec '05 Proceedings of the 7th workshop on Multimedia and security
Robust frequency domain audio watermarking: a tuning analysis
IWDW'04 Proceedings of the Third international conference on Digital Watermarking
Information-theoretic analysis of security in side-informed data hiding
IH'05 Proceedings of the 7th international conference on Information Hiding
Spread-spectrum watermarking of audio signals
IEEE Transactions on Signal Processing
Attacks on digital watermarks: classification, estimation based attacks, and benchmarks
IEEE Communications Magazine
Secure spread spectrum watermarking for multimedia
IEEE Transactions on Image Processing
Digital audio watermarking evaluation within the application field of perceptual hashing
Proceedings of the 2008 ACM symposium on Applied computing
How to Compare Image Watermarking Algorithms
Transactions on Data Hiding and Multimedia Security IV
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Digital watermarking is a growing research area to mark digital content (image, audio, video, etc.) by embedding information into the content itself. This technique opens or provides additional and useful features for many application fields (like DRM, annotation, integrity proof and many more). The role of watermarking algorithm evaluation (in a broader sense benchmarking) is to provide a fair and automated analysis of a specific approach if it can fulfill certain application requirements and to perform a comparison with different or similar approaches. Today most algorithm designers use their own methodology and therefore the results are hardly comparable. Derived from the variety of actually presented evaluation procedures in this paper, firstly we introduce a theoretical framework for digital robust watermarking algorithms where we focus on the triangle of robustness, transparency and capacity. The main properties and measuring methods are described. Secondly, a practical environment shows the predefined definition and introduces the practical relevance needed for robust audio watermarking benchmarking. Our goal is to provide a more partial precise methodology to test and compare watermarking algorithms. The hope is that watermarking algorithm designers will use our introduced methodology for testing their algorithms to allow a comparison with existing algorithms more easily. Our work should be seen as a scalable and improvable attempt for a formalization of a benchmarking methodology in the triangle of transparency, capacity and robustness.