Computational secret image sharing (CSIS) is an effective way to protect a secret image during its transmission and storage, and thus it has attracted lots of attentions since its appearance. Nowadays, it has become a hot topic for researchers to improve the embedding capacity and eliminate the underflow and overflow situations, which is embarrassing and difficult to deal with. The scheme, which has the highest embedding capacity among the existing schemes, has the underflow and overflow problems. Although the underflow and overflow situations have been well dealt with by different methods, the embedding capacities of these methods are reduced more or less. Motivated by these concerns, we propose a novel scheme, in which we take the differential coding, Huffman coding, and data converting to compress the secret image before embedding it to further improve the embedding capacity, and the pixel mapping matrix embedding method with a newly designed matrix is used to embed secret image data into the cover image to avoid the underflow and overflow situations. Experiment results show that our scheme can improve the embedding capacity further and eliminate the underflow and overflow situations at the same time.
Compared with the visual-cryptography-based visual secret sharing, the random-grid-based visual secret sharing (RGVSS) has some technical advantages, such as no pixel expansion and no need of codebooks. Designed based on RGVSS, the user-friendly random-grid-based visual secret sharing (UFRGVSS) not only inherits the advantages of RGVSS but also overcomes the data management problem in RGVSS by taking meaningful images as shares. Unfortunately, up to now, the existing threshold UFRGVSS schemes are only (2, 2) ones, which should use two meaningful images with complementary colors as shares. What's more, there is no feasible method to construct UFRGVSS schemes for more general threshold access structures excluding (2, 2) threshold, let alone for general access structures (GASs). Motivated by these concerns, in this paper, by stamping the gray-scale images with the shares generated from the traditional RGVSS, a novel method was proposed to design the UFRGVSS scheme for GASs, in which the resulting shares can be any meaningful gray-scale images. Experimental results show the feasibility of the proposed method by assessing its performance under different situations. Literature retrieval shows that our work may be the first attempt to construct the UFRGVSS scheme for GASs.
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