A Channel-Dependent Statistical Watermark Detector for Color Images
Data security is a main concern in everyday data transmissions over the Internet. A possible solution to guarantee secure and legitimate transaction is via hiding a piece of tractable information into the multimedia signal, that is, watermarking. In this paper, we propose a new color image watermarking scheme and its corresponding detector in the sparse domain. The watermark detector aims at verifying the ownership and circumventing any unauthorized duplication of the digital data. Most of the existing color image watermarking schemes disregard the inter-channel dependencies. In view of this, we take into account the interchannel dependencies between RGB channels and interscale dependencies of the sparse coefficients of color images by employing the hidden Markov model. An efficient detector is designed by establishing a binary hypothesis test through which the existence of the hidden watermark is examined. Experiments are conducted to evaluate the performance of the proposed watermark detector for color images. The results show that the proposed detector provides detection rates higher than those provided by the other detectors, even in the presence of attacks. It is also shown that the proposed detector exhibits better performance in terms of the robustness of the embedded watermark.