Gradual Improvements in the Visual Quality of the Thin Lines Within the Random Grid Visual Cryptography Scheme

The visual cryptography scheme (VCS) is a fundamental image encryption technique that divides a secret image into two or more shares, such that the original image can be revealed by superimposing a sufficient number of shares. A major limitation of conventional VCS methods is pixel expansion, wherein the generated shares and reconstructed image are typically at least twice the size of the original. Additionally, thin lines or curves—only one pixel wide in the original image—often appear distorted or duplicated in the reconstructed version, a distortion known as the thin-line problem (TLP). To eliminate the reliance on predefined codebooks inherent in traditional VCS, Kafri introduced the Random Grid visual cryptography scheme (RG-VCS), which eliminates the need for such codebooks. This paper introduces novel algorithms that are among the first to explicitly address the thin-line problem in the context of random grid based schemes. This paper presents novel visual cryptography algorithms specifically designed to address the thin-line preservation problem (TLP), which existing methods typically overlook. A comprehensive visual and numerical comparison was conducted against existing algorithms that do not explicitly handle the TLP. The proposed methods introduce adaptive encoding strategies that preserve fine image details, fully resolving TLP-2 and TLP-3 and partially addressing TLP-1. Experimental results show an average improvement of 18% in SSIM and 13% in contrast over existing approaches. Statistical t-tests confirm the significance of these enhancements, demonstrating the effectiveness and superiority of the proposed algorithms.