Visual cryptography is kind of cryptography that can be decoded directly by the human visual system without any calculation. It finds many applications in cryptographic field such as key management, message concealment, authorization, authentication, identification, and entertainment. Given a visually recognizable target image, the (n, k) encryption scheme is to cryptologically decompose the image into a set of n shares, called shadow images, which are recorded in transparencies, such that the pictorial meaning stored in the original image is recognizable if and only if a viewer is able to acquire at least k shares and stack them together.
Traditionally, a codebook approach was used to produce shares for the
instances of an encryption scheme. This implies that different access
schemes require different codebooks. The size of shares are larger than target
images. We we propose a neural network approach for visual cryptography. The NN
model to conduct this research is the so-called quantum neural networks (Q'tron
NNs). For encrypting, the target(s) image input to the NN is (are) gray image(s).
After the NN settles down, a set of binary shadow images, each of them has the
same size as
the target, will be produced. By stacking enough number of the shadow images, the superposed version will be a halftone images to mimic the target image. We also apply Q'tron NN to visual authorization. Some experimental results and demo with Java applet are displayed on this page.
A more formal and detailed description of Visual Cryptography Scheme can be found in these papers.