GA-Based Robustness Evaluation Method for Digital Image Watermarking

摘要

The present paper proposes a new flexible and effective evaluation tool based on genetic algorithms to test the robustness of digital image watermarking techniques. Given a set of possible attacks, the method finds the best possible un-watermarked image in terms of Weighted Peak Signal to Noise Ratio (WPSNR). In fact, it implements a stochastic search of the optimal parameters to be assigned to each processing operation in order to find the combined attack that removes the watermark while producing the smallest possible degradation of the image in terms of human perception. As a result, the proposed method makes it possible to assess the overall performance of a watermarking scheme, and to have an immediate feedback on its robustness to different attacks. A set of tests is presented, referring to the application of the tool to two known watermarking approaches.