Proceedings Article | 29 April 2002
KEYWORDS: Digital watermarking, Medical imaging, Image quality, Video, Distortion, Video compression, Detection and tracking algorithms, Image compression, Wavelets, Denoising
The Checkmark benchmarking tool was introduced to provide a framework for application-oriented evaluation of watermarking schemes. In this article we introduce new attacks and applications into the existing Checkmark framework. In addition to describing new attacks and applications, we also compare the performance of some well-known watermarking algorithms (proposed by Bruyndonckx,Cox, Fridrich, Dugad, Kim, Wang, Xia, Xie, Zhu and Pereira) with respect to the Checkmark benchmark. In particular, we consider the non-geometric application which contains tests that do not change the geometry of image. This attack constraint is artificial, but yet important for research purposes since a number of algorithms may be interesting, but would score poorly with respect to specific applications simply because geometric compensation has not been incorporated. We note, however, that with the help of image registration, even research algorithms that do not have counter-measures against geometric distortion -- such as a template or reference watermark -- can be evaluated. In the first version of the Checkmark benchmarking program, application-oriented evaluation was introduced, along with many new attacks not already considered in the literature. A second goal of this paper is to introduce new attacks and new applications into the Checkmark framework. In particular, we introduce the following new applications: video frame watermarking, medical imaging and watermarking of logos. Video frame watermarking includes low compression attacks and distortions which warp the edges of the video as well as general projective transformations which may result from someone filming the screen at a cinema. With respect to medical imaging, only small distortions are considered and furthermore it is essential that no distortions are present at embedding. Finally for logos, we consider images of small sizes and particularly compression, scaling, aspect ratio and other small distortions. The challenge of watermarking logos is essentially that of watermarking a small and typically simple image. With respect to new attacks, we consider: subsampling followed by interpolation, dithering and thresholding which both yield a binary image.
