Halftone-Image Security Improving Using Overall Minimal-Error Searching
For image-based data hiding, it is difficult to achieve good image quality when high embedding capacity and 100% data extraction are also demanded. In this study, the proposed method, namely, overall minimal-error searching (OMES) is developed to meet the aforementioned requirements. Moreover, the concept of secret sharing is also adopted to distribute watermarks into multiple halftone images, and the embedded information can only be extracted when all of the marked images are gathered. The OMES modifies the halftone values at the same position of all host images with the trained substitution table (S-Table). The S-Table makes the original combination of these halftone values as another meaningful combination for embedding watermark, which is the key part in determining the image quality. Thus, an optimization procedure is proposed to achieve the optimized S-Table. Two different encoders, called error-diffused-based and least-mean-square-based approaches are also developed to cooperate with the proposed OMES to cope with high processing speed and high image quality applications, respectively. Finally, for resisting the issues caused by the print-and-scan attack, such as zooming, rotation, and dot gain effect, a compensation correction procedure is also proposed. As demonstrated in the experimental results, the proposed approach provides good image quality, and is able to guard against some frequent happened attacks in printing applications.
halftoning data hiding digital watermarking error diffusion (ed) least mean square (lms)