This paper proposes a polynomial-style region incremental multisecret image sharing (PBRIMSIS), for sharing multiple secrets in an image among n participants. The method enables the dealer to distribute the content of an image S to multiple regions, where each region is associated with a certain level of secrecy. In the proposed n-level PBRIMSIS scheme, input image S is encoded to n+1 shadow images that exhibit the following features: a. each shadow image cannot reveal any region in S, b. any t (2 ⩽ t ⩽ n + 1) shadow images can be used to reveal these regions associated with up to t - 1 secret levels, and c. S can be completely reconstructed when all of the n+1 shadow images are available. A discrete cosine transform-based PBRIMSIS with a smaller shadow image scheme is designed to improve the transmission and storage of the generated shadow images. The property of incremental disclosure to the region-based secrets in an image is applicable to image sharing in diverse applications that require the sharing of multiple secrets with different secrecy priorities, such as in cooperative working or in military secrets.
This paper proposes a visual cryptography (VC) by a random grid (RG) scheme with identifiable shares. The method encodes an image O in two shares that exhibits the following features: 1. each generated share is a RG with the same scale as O; 2. any share singly reveals no secret information on O; 3. the secrets can be revealed by superimposing the two generated shares; 4. folding up a share will display the identification patterns associated with it; and 5. both of the secret information and the identification patterns are recognized by the naked eye without any computation. The property to show identification patterns by simply folding it up is novel to visual cryptographic schemes in the literature. It provides useful information to identify the pair of shares belonging to a secret image, and establishes a simple and friendly interface for users to distinguish among and manage the numerous shares created by VC schemes.
The successive elimination algorithm (SEA) has already proved successful in block motion estimation. This paper presents a simple and efficient algorithm called the threshold-based SEA as a search engine to take advantage of the simplicity of the SEA while avoiding its redundant computation. In addition, the threshold-based SEA utilizes a threshold adaptation mechanism to efficiently distribute the available computational power of the employed codec to blocks of video sequences. Since the threshold-based approach is performed at each search candidate block, it can be combined not only with the SEA but also with other fast algorithms, including the three-step search, the block-based gradient descent search, and the diamond search. Depending on the motion activity in the sequences, experimental results indicate that the threshold-based approach can uniformly achieve a quality improvement over the original SEA for the same computation.