An advantage of steganography, as opposed to other information hiding techniques, is that the embedder can select a cover image that results in the least detectable stego image. In a previously proposed method, a technique based on block texture similarity was introduced where blocks of cover image were replaced with the similar secret image blocks; then indices of secret image blocks were stored in cover image. In this method, the blocks of secret image are compared with blocks of a set of cover images and the image with most similar blocks to those of the secret image is selected as the best candidate to carry the secret image. Using appropriate features for comparing image blocks, guaranties higher quality of stego images and consequently, allows for higher embedding capacity, less delectability and, enhanced security. Based on this idea, in this paper, an adaptive cover selection steganography method is proposed, that uses statistical features of image blocks and their neighborhood Using the block neighborhood information, we prevent appearing virtual edges in the sides and corners of the replaced blocks. Our method is examined with feature based and wavelet based steganalysis algorithms. The results prove the effectiveness and benefits of the proposed method.
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