Robust watermarking against print and scan attack through efficient modeling algorithm

This article proposes a blind discrete wavelet transform-discrete cosine transform (DWT-DCT) composite watermarking scheme that is robust against print and scan distortions. First, two-dimensional DWT is applied to the original image to obtain the mid-frequency subbands. Then, a one-dimensional DCT is applied to the selected mid-frequency subbands to extract the final coefficients for embedding the watermark. To specify watermarking parameters, we utilize a Genetic Algorithm to achieve a predefined image quality after watermark insertion. Suitable locations for watermarking are determined by analyzing the effect of a modeling algorithm. This model simulates noise and nonlinear attacks in printers and scanners through noise estimation and system identification methods. The experimental results demonstrate that the proposed algorithm has a high robustness against print and scan attack such that its robustness is higher than related watermarking algorithms. A neural network as a nonlinear system models print and scan distortions properly.An accurate model could suggest suitable locations in DWT domain for watermarking.Watermarking in the combination of DWT and DCT domains will improve the robustness.Only downsampling attack will degrade the robustness of watermarking algorithm.