Raster map is an image that has been discretized in space and brightness, and it is an important carrier of geospatial data. With the rapid development of Internet and big data technologies, preserving the privacy of raster map has become an urgent task. To solve these issues, we propose a novel extended visual cryptography scheme to securely store a raster map into other two meaningful halftone maps in the paper. The scheme avoids the random-looking shares of visual cryptography schemes which are vulnerable and hard to manage. We first apply the halftone and color decomposition methods to transform a color secret map into halftone images. After that, we encode the secret map block by block to avoid pixel expansion. At last, by optimizing the selection of encrypted blocks, we achieve a high-quality secret recovery from generated multiple equal-sized shares. The technique used is to employ a versatile and secure raster map exchange. Experimental results show that, compared with previous work, the proposed scheme significantly improves the performance of recovered raster maps.

Benefiting from the development of the Internet and smart devices, it is now convenient to transmit images anywhere and anytime, which poses a new challenge for image security. The Visual Cryptography Scheme (VCS) is a secret sharing method for protecting an image without a key, the merit of VCS is the human visual system (HVS) can restore the secret image by simply superimposing qualified shares, without any computation. To eliminate noise-like shares in traditional VCS, this paper presents a novel QR code-based expansion-free and meaningful visual cryptography scheme (QEVCS), which generates visually appealing QR codes for transmitting meaningful shares. When distributing on public networks, this scheme does not attract the attention of potential attackers. By limiting the gray-level of a halftoned image, QEVCS both keep the computation-free of visual cryptography and the size of recovery image same as the secret images. The experimental results show the effectiveness of QEVCS when preserving the privacy of images.

Porous structures are kinds of structures with excellent physical properties and mechanical characteristics through components and internal structure. However, the irregular internal morphology of porous structures poses new challenges to product modeling techniques. Traditional computer-aided design (CAD) modeling methods can only represent the external geometric and topological information of models, lacking the description of the internal structure and conformation, which limits the development of new porous products. In this paper, a new simple and effective modeling method for 3D irregular porous structures is proposed, which improves the controllability of pore shape and porosity, thus overcoming the limitations of existing methods in 3D and concave structures. The key idea is to solve isothermal for modeling the porosity of porous units. Experimental results show that the method can easily obtain smooth and approximate porous structures from arbitrary irregular 3D surfaces.