A possible solution to the difficult problem of geometrical distortion of watermarked images in a blind watermarking
scenario is to use a template grid in the autocorrelation function. However, the important drawback of this method is
that the watermark itself can be estimated and subtracted, or the peaks in the Fourier magnitude spectrum can be
removed. A recently proposed solution is to modulate the watermark with a pattern derived from the image content and
a secret key. This effectively hides the watermark pattern, making malicious attacks much more difficult. However, the
algorithm to compute the modulation pattern is computationally intensive. We propose an efficient implementation,
using frequency domain filtering, to make this hiding method more practical. Furthermore, we evaluate the performance
of different kinds of modulation patterns. We present experimental results showing the influence of template hiding on
detection and payload extraction performance. The results also show that modulating the ACF based watermark
improves detection performance when the modulation signal can be retrieved sufficiently accurately. Modulation signals
with small average periods between zero crossings provide the most watermark detection improvement. Using these
signals, the detector can also make the most errors in retrieving the modulation signal until the detection performance
drops below the performance of the watermarking method without modulation.
One way of recovering watermarks in geometrically distorted images is by performing a geometrical search. In addition to the computational cost required for this method, this paper considers the more important problem of false positives. The maximal number of detections that can be performed in a geometrical search is bounded by the maximum false positive detection probability required by the watermark application. We show that image and key dependency in the watermark detector leads to different false positive detection probabilities for geometrical searches for different images and keys. Furthermore, the image and key dependency of the tested watermark detector increases the random-image-random-key false positive detection probability, compared to the Bernoulli experiment that was used as a model.