A copyright-protection watermark mechanism based on generalized brain-state-in-a-box neural network and error diffusion halftoning
Fan Li, Tiegang Gao, Qunting Yang, Yanjun Cao · 2011
A publicly verifiable scheme for the copyright protection of digital image is proposed in this paper. Combining with some cryptographic techniques such as digital signature and timestamp, the scheme features an idea of registering watermark information to a trusted authority (TA) rather than embedding it into the host image, which overcomes many deficiencies of the conventional watermarking algorithm. In the scheme, generalized brain-state-in-a-box neural network (gBSB) and error diffusion halftoning are employed to extract the robust feature, which is further used to generate the verification information registered to TA, from the original image. Experimental results demonstrate that the feature is adequately robust to make sure that the verifier will be able to extract the logo mark from the attacked image correctly. The proposed scheme is competent to be applied to the copyright protection of digital multimedia.