Print-scan invariant text image watermarking for hardcopy document authentication

In this paper, a novel contour feature-based text image watermarking scheme against print and scan processes is proposed. We employ a mathematical multiplicative transformation model to approximate the geometric invariant feature that can survive a variety of attacks during the print-scan process and thus serve as reference points for both watermark embedding and extraction. Based on the print-scan invariant, the boundary points of each character are flipped using Fourier descriptors with visual perception characteristics, so that the watermarks are embedded into the visually nonsignificant points. In the calculation process of the print-scan invariant, a certain text line serves as the benchmark line without affording additional characters for watermark adjustment. Thus, the hiding capacity is greatly improved. For the data detection, noise reduction and deskewing mechanisms are performed previously to compensate for the distortions caused by hardcopy. The watermark is then extracted by parity check of the invariant feature of connected components for soft authentication. The experimental results show that the proposed approach is not limited to a particular language, and has better robustness, watermark transparency as well as hiding capacity compared with some existing methods.