Adaptive Color Image Watermarking Algorithm Based on Fractal and Neural Networks

In this paper, a color image watermarking algorithm based on fractal and neural networks in Discrete Cosine Transform (DCT) domain is proposed. Firstly, the algorithm utilizes the fractal image coding technique to obtain the characteristic data of a gray-level image watermark signal and encrypts it by a symmetric encryption algorithm before it was embedded. Secondly, by exploiting the abilities of neural networks and considering the characteristics of Human Visual System (HVS), a Just Noticeable Difference (JND) threshold controller is designed to ensure the strength of the embedded data adapting to the host image itself entirely. Thus the watermark scheme possesses the dual security characteristics. To improve the robustness of the algorithm, the simple and repetition of the results is applied to watermark configuration. And the CIELab color space is chosen to guarantee the stability of the results. Experimental results show that the proposed algorithm is invisible and robust against commonly used image-processing methods.