This paper addresses feature extraction techniques for robust watermarking.
Geometric distortion attacks desynchronize the location of the inserted
watermark and hence prevent watermark detection. Watermark synchronization,
which is a process of finding the location for watermark insertion and detection,
is crucial to design robust watermarking. One solution is to use image features.
This paper reviews feature extraction techniques that have been used in featurebased
watermarking: the Harris corner detector and the Mexican Hat wavelet
scale interaction method. We also evaluate the scale-invariant keypoint extractor
in comparison with other techniques in aspect of watermarking. After feature
extraction, the set of triangles is generated by Delaunay tessellation. These
triangles are the location for watermark insertion and detection. Redetection ratio
of triangles is evaluated against geometric distortion attacks as well as signal
processing attacks. Experimental results show that the scale-invariant keypoint
extractor is appropriate for robust watermarking.