PROJECT TITLE :

Improving the Visual Quality of Size-Invariant Visual Cryptography for Grayscale Images An Analysis-by-Synthesis (AbS) Approach

ABSTRACT:

Picture size reduction leads to poor perceptual quality for the secret image in VC for grayscale images. We're working on VC algorithms for binary images and measures that don't exactly correlate to how humans view halftone images in order to increase the quality. An error diffusion method feeds back and compensates for the difference between encoded and reconstructed secret pictures simultaneously, which we call an analysis-by-synthesis (AbS) framework for halftoning and VC encoder integration. As a result of this, a visually appealing reconstructed secret image can be created by pushing the error between the secret and the original secret into the high frequency range. There are numerous existing size-invariant VC algorithms that can be used with this framework, such as random grid VC, vector/block VC, and probabilistic VC. It has been proven that the AbS framework is just as secure compared to other well-known VC algorithm implementations. The proposed AbS framework has been tested and shown to be effective.