Modified Deterministic Approach for Size Invariant Visual Secret Sharing with Improved Quality of Recovered Secret

Abstract In the digital world, securing data is very significant. Digital data can focus either on content secrecy or the quality of recovered secret content. Visual Secret Sharing (VSS) becomes vital when content secrecy is essential over quality. VSS encrypts the secret into “n” share. The individual share cannot reveal any information; the secret gets revealed only when a predefined number of shares come together. Earlier attempted probabilistic and random grid approaches of size invariant VSS compromise in quality of recovered secret. Paper presents a method as a modified deterministic approach for size invariant VSS with improved quality of recovered secret; giving minimum Mean Squared Error (MSE), maximum Peak Signal to Noise Ratio (PSNR), and Structural Similarity Index (SSIM) close to “1” as compared to other existing methods.