Hybrid pixel-based data hiding and block-based watermarking for error-diffused halftone images

A low computational complexity noise-balanced error diffusion (NBEDF) technique is proposed for embedding watermark into error-diffused images. The visual decoding pattern can be perceived when two or more similar NBEDF images are overlaid each other, even in a high activity region. Furthermore, with the modified improved version of NBEDF, the two halftone images can be made from two total different gray-tone images and still provide a clear and sharp visual decoding pattern. With the self-decoding techniques, we can also decode the pattern by only one NBEDF image. However, the NBEDF method is not so robust to the damage due to printing or other distortions. Thus, a kernels-alternated error diffusion (KAEDF) technique is proposed. We find that the two well-known kernels proposed by Jarvis et al. and Stucki are very compatible by alternately using them in halftone process. In the decoder, because the spectral distribution of Jarvis and Stucki kernels are different in the 2-D fast Fourier transform domain, we use the cumulative squared Euclidean distance criterion to determine each cell in a watermarked halftone image either belonging to Jarvis or Stucki, and then decode the watermark. Furthermore, because of the detailed textures of Jarvis and Stucki patterns are somewhat different in spatial domain, the lookup table (LUT) technique is also used for fast decoding. From the simulation results, the correct decoding rates using both techniques are high and extremely robust, even after printing and scanning processes. Finally, we extend the hybrid NBEDF and KAEDF algorithms to two color EDF halftone images, where eight independent KAEDF watermarks and 16 NBEDF watermarks can be inserted and still achieve a high-quality result.