Digital watermarking techniques have been used to assert the ownerships of digital images. The ownership information is embedded in an image as a watermark so that the owner of the image can be identified. However, many types of attacks have been used in attempts to break or remove embedded watermarks. Therefore, the watermark should be very robust against various kinds of attacks. Among them, the print-and-scan (PS) attack is very challenging because it not only alters the pixel values but also changes the positions of the original pixels. In this paper, we propose a watermarking system operating in the discrete cosine transform (DCT) domain. The polarities of the DCT coefficients are modified for watermark embedding. This is done by considering the properties of DCT coefficients under the PS attack. The proposed system is able to maintain the image quality after watermarking and the embedded watermark is very robust against the PS attack as well.

This paper presents a non-blind watermarking technique that is robust to non-linear geometric distortion attacks. This is one of the most challenging problems for copyright protection of digital content because it is difficult to estimate the distortion parameters for the embedded blocks. In our proposed scheme, the location of the blocks are recorded by the translation parameters from multiple Scale Invariant Feature Transform (SIFT) feature points. This method is based on two assumptions: SIFT features are robust to non-linear geometric distortion and even such non-linear distortion can be regarded as “linear” distortion in local regions. We conducted experiments using 149,800 images (7 standard images and 100 images downloaded from Flickr, 10 different messages, 10 different embedding block patterns, and 14 attacks). The results show that the watermark detection performance is drastically improved, while the baseline method can achieve only chance level accuracy.