Visual cryptography for general access structures
Information and Computation
Extended capabilities for visual cryptography
Theoretical Computer Science
Visual cryptography for gray-level images by dithering techniques
Pattern Recognition Letters
New visual secret sharing schemes using probabilistic method
Pattern Recognition Letters
Image encryption by random grids
Pattern Recognition
Colored visual cryptography without color darkening
Theoretical Computer Science
Image encryption by multiple random grids
Pattern Recognition
Visual secret sharing by random grids revisited
Pattern Recognition
Reversibility improved lossless data hiding
Signal Processing
Halftone visual cryptography via error diffusion
IEEE Transactions on Information Forensics and Security
Step construction of visual cryptography schemes
IEEE Transactions on Information Forensics and Security
A novel colour image encryption algorithm based on chaos
Signal Processing
Improving the visual quality of size invariant visual cryptography scheme
Journal of Visual Communication and Image Representation
Yet another multiple-image encryption by rotating random grids
Signal Processing
IEEE Transactions on Image Processing
Color Extended Visual Cryptography Using Error Diffusion
IEEE Transactions on Image Processing
Embedded Extended Visual Cryptography Schemes
IEEE Transactions on Information Forensics and Security
XOR-based meaningful visual secret sharing by generalized random grids
Proceedings of the first ACM workshop on Information hiding and multimedia security
Improved tagged visual cryptography by random grids
Signal Processing
Hi-index | 0.08 |
Pixel expansion and visual quality of the revealed secret image are two major concerns in visual secret sharing (VSS). Random grid (RG) is an alternative approach to solve the pixel expansion problem by making the share as big as the original secret image, at the expense of sacrificing the visual quality of the reconstructed secret image. In this paper, two algorithms, including a contrast-enhanced RG-based VSS and a void-and-cluster-based (VAC-based) post-processing, are introduced to improve the reconstructed image quality. Experimental results and theoretical analysis are provided, illustrating that competitive visual quality is obtained by combined use of the two proposed methods.