A neural-network approach for visual cryptography and authorization

In this paper, we propose a neural-network approach for visual authorization, which is an application of visual cryptography (VC). The scheme contains a key-share and a set of user-shares. The administrator owns the key-share, and each user owns a user-share issued by the administrator from the user-share set. The shares in the user-share set are visually indistinguishable, i.e. they have the same pictorial meaning. However, the stacking of the key-share with different user-shares will reveal significantly different images. Therefore, the administrator (in fact, only the administrator) can visually recognize the authority assigned to a particular user by viewing the information appearing in the superposed image of key-share and user-share. This approach is completely different from traditional VC approaches. The salient features include: (i) the access schemes are described using a set of graytone images, and (ii) the codebooks to fulfil them are not required; and (iii) the size of share images is the same as the size of target image.