Extended capabilities for visual cryptography

By Giuseppe Ateniese, C. Blundo, Alfredo De Santis, Douglas R Stinson. Theoretical Computer Science, 2001

485 citations recorded by the source corpus.

Subfields: Computer Vision and Pattern Recognition, Electrical and Electronic Engineering

View Paper: https://www.semanticscholar.org/paper/e8d45d7914420dcdc987e001477f9e515d08bb3a

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Computer Vision and Pattern Recognition

1. Zhongmin Wang
2. Gonzalo R. Arce
3. Giovanni Di Crescenzo
4. Brent Waters

In Electrical and Electronic Engineering

1. Gonzalo R. Arce
2. Zhongmin Wang
3. Giovanni Di Crescenzo

Citations in the corpus

• Halftone Visual Cryptography Via Error Diffusion (2009, methodology): “Any qualified set of participants can visually de-code , but a forbidden set of participants has no information of [8], [18].”
• Halftone visual cryptography (2006, background): “In the above procedure, the selection of the secret information pixels in a halftone cell is important as it affects the visual quality of the resultant halftone shares.”