While Digital Watermarking has received much attention within the academic community and private sector in recent years, it is still a relatively young technology. As such, there are few accepted tools and metrics that can be used to validate the performance claims asserted by members of the research community and evaluate the suitability of a watermarking technique for specific applications. This lack of a universally adopted set of metrics and methods has motivated us to develop a web-based digital watermark evaluation system known as the Watermark Evaluation Testbed or WET. This system has undergone several improvements since its inception. The ultimate goal of this work has been to develop a platform, where any watermarking researcher can test not only the performance of known techniques, but also their own techniques. This goal has been reached by the latest version of the system. New tools and concepts have been designed to achieve the desired objectives. This paper describes the new features of WET. Moreover, we also summarize the development process of the entire project as well as introduce new directions for future work.
While Digital Watermarking has received much attention in recent
years, it is still a relatively young technology. There are few
accepted tools/metrics that can be used to evaluate the suitability
of a watermarking technique for a specific application. This lack of
a universally adopted set of metrics/methods has motivated us to
develop a web-based digital watermark evaluation system called the
Watermark Evaluation Testbed or WET. There have been
more improvements over the first version of WET. We
implemented batch mode with a queue that allows for user submitted
jobs. In addition to StirMark 3.1 as an attack module, we added
attack modules based on StirMark 4.0. For a new image fidelity
measure, we evaluate conditional entropy as an image fidelity
measure for different watermarking algorithms and different attacks.
Also, we show the results of curve fitting the Receiver Operating
Characteristic (ROC) analysis data using the Parzen window density
estimation. The curve fits the data closely while having only two
parameters to estimate.
We describe a blind watermarking technique for digital images. Our technique constructs an image-dependent watermark in the discrete wavelet transform (DWT) domain and inserts the watermark in the most signifcant coefficients of the image. The watermarked coefficients are determined by using the hierarchical tree structure induced by the DWT, similar in concept to embedded zerotree wavelet (EZW) compression. If the watermarked image is attacked or manipulated such that the set of significant coefficients is changed, the tree structure allows the correlation-based watermark detector to recover synchronization.
Our technique also uses a visual adaptive scheme to insert the watermark to minimize watermark perceptibility. The visual adaptive scheme also takes advantage of the tree structure. Finally, a template is inserted into the watermark to provide robustness against geometric attacks. The template detection uses the cross-ratio of four collinear points.
While digital watermarking has received much attention within the academic community and private sector
in recent years, it is still a relatively young technology. As such there are few widely accepted benchmarks
that can be used to validate the performance claims asserted by members of the research community. This
lack of a universally adopted benchmark has hindered research and created confusion within the general public.
To facilitate the development of a universally adopted benchmark, we are developing at Purdue University a
web-based system that will allow users to evaluate the performance of watermarking techniques. This system
consists of reference software that includes both watermark embedders and watermark detectors, attack scenarios,
evaluation modules and a large image database. The ultimate goal of the current work is to develop a platform
that one can use to test the performance of watermarking methods and obtain fair, reproducible comparisons
of the results. We feel that this work will greatly stimulate new research in watermarking and data hiding by
allowing one to demonstrate how new techniques are moving forward the state of the art. We will refer to this
system as the Watermark Evaluation Testbed or WET.