Watermarking via optimization algorithms for quantizing ran- domized statistics of image regions

We introduce a novel approach for blind signal watermarking and apply it to images. We derive randomized robust semi-global features in a suitable transform domain (wavelets in case of images) and quantize them in order to embed the watermark. Quantization is carried out by adding an embedding sequence to the host; this sequence is computed by solving an optimization problem whose parameters are known to the information hider, but unknown to the attacker. We experimentally identify some conditions (our randomizations are aimed at achieving them) satisfied by our parameters, which formally and experimentally imply robustness of our algorithm against malicious optimal estimation attacks. We also tested its robustness against many generic (i.e. non-malicious benchmark attacks ) attacks.