A DWT Domain Image Watermarking Scheme Using Genetic Algorithm and Synergetic Neural Network

A DWT domain image watermarking scheme is proposed in this paper to meet the watermarking properties: security, imperceptibility and robustness. In the scheme, watermark comes from a meaningful binary image encrypted by two-dimensional chaotic stream encryption that has more security. In the procedure of watermark embedding, the watermark is embedded into host image through selecting and modifying the wavelet coefficients using Genetic algorithm with a simple fitness function to improve the imperceptibility of watermarked image. In order to identify the owner of extracted watermark, Synergetic Neural Network is used in the watermarking identification to overcome the limitation of correlation analysis or the human sense organ after some attacks. The results of our scheme realization and robust experiments show that this scheme has preferable performance.