Cover Selection Steganography via Run length matrix and Human Visual System

In this paper, A novel approach of cover selection for steganography is proposed based on image texture features and human visual system. Our proposed algorithm employs run length matrix to extract some proper images from a huge image database by using image texture features and creates stego version of selected images after embedding process. Then, it computes similarity between original proper selected images and their stego versions by using structural similarity as image quality metric to select one image with maximum similarity to its stego as the best cover. According to the results of composing our new proposed cover selection algorithm with other steganography methods, it is confirmed that the proposed algorithm is able to increase the stego quality. We also evaluate the robustness of our algorithm over steganalysis methods such as Wavelet based and Block based steganalyses; The experimental results show that the proposed approach is greatly valuable in decreasing recognition risk of hidden information.