# Integrating Visual Cryptography for Efficient and Secure Image Sharing on Social Networks
## 4 Experimental Results
### Experiment Results
Halftoning inherently reduces the quality of the image by converting continuous-tone images into  
Figure 3: Stacking results for kinds of VCSs. Each column corresponds to one algorithm and each row corresponds to one classic image. From left to right are our, random-grid, probabilistic, block, and error diffusion-based VCSs. From bottom to top are test images including airplane, baboon, Barbara, boats, peppers, butterfly, and house. binary representations. This process, while necessary for the VC encryption scheme, introduces a fundamental limit on the achievable image quality post-decryption. In our experiments, despite the application of different encryption methods--ED, probabilistic, our method, and random-grid--the foundational halftoning step has already imparted a degree of image degradation. The subsequent VC encryption, which involves the overlay of black pixels, further darkens the decrypted image. Consequently, while our proposed method and other improvements aim to enhance image quality, the room for enhancement is inherently constrained by the preceding halftoning process. Our quantitative experiments, which include metrics such as PSNR, SSIM, and NAE, are sensitive measures of image quality and similarity. The small differences in these metrics reflect the limited scope for improvement within the constraints imposed by the halftoning and VC encryption process. Even though our method and other advanced techniques have managed to incrementally improve upon the baseline, the improvements are moderate due to the aforementioned reasons. For social networks, numerous devices need to acquire and transmit sensitive information while ensuring its confidentiality. Digital images rich in privacy information are vulnerable to interception, tampering, and theft when transmitted over public channels or networks. Ensuring the secure transmission, application, and storage of image privacy has become a challenging issue in building information security frameworks. However, these \begin{table}
\begin{tabular}{l l l l l} \hline
**Test Images \(\downarrow\)** & **Metrics \(\rightarrow\)** & **PSNR** & **SSIM** & **NAE** \\ \hline \multirow{4}{*}{Baboon} & ED & 20.52 & 0.83 & 0.36 \\  & probabilistic & 13.06 & 0.47 & 0.58 \\  & Our & **19.69** & **0.69** & **0.39** \\  & random-grid & 10.67 & 0.56 & 0.64 \\ \hline \multirow{4}{*}{Barbara} & ED & 21.41 & 0.83 & 0.36 \\  & probabilistic & 12.79 & 0.44 & 0.62 \\  & Our & **20.54** & **0.72** & **0.40** \\  & random-grid & 11.24 & 0.52 & 0.65 \\ \hline \multirow{4}{*}{Boats} & ED & 20.25 & 0.82 & 0.36 \\  & probabilistic & 13.09 & 0.45 & 0.58 \\  & Our & **19.28** & **0.7** & **0.39** \\  & random-grid & 10.91 & 0.56 & 0.63 \\ \hline \multirow{4}{*}{Butterfly} & ED & 20.83 & 0.83 & 0.36 \\  & probabilistic & 12.93 & 0.48 & 0.6 \\  & Our & **19.99** & **0.74** & **0.39** \\  & random-grid & 12.15 & 0.6 & 0.61 \\ \hline \multirow{4}{*}{Peppers} & ED & 20.68 & 0.83 & 0.36 \\  & probabilistic & 12.96 & 0.44 & 0.6 \\  & Our & **20.00** & **0.72** & **0.39** \\  & random-grid & 11.51 & 0.55 & 0.63 \\ \hline \multirow{4}{*}{House} & ED & 19.72 & 0.83 & 0.36 \\  & probabilistic & 13.08 & 0.48 & 0.56 \\  & Our & **18.87** & **0.68** & **0.39** \\  & random-grid & 10.83 & 0.58 & 0.62 \\ \hline \multirow{4}{*}{Airplane} & ED & 17.82 & 0.81 & 0.36 \\  & probabilistic & 13.62 & 0.53 & 0.48 \\ \cline{1-1}  & Our & **17.24** & **0.65** & **0.38** \\ \cline{1-1}  & random-grid & 11.92 & 0.69 & 0.52 \\ \hline \end{tabular}
\end{table} 
Table 1: Comparing four stacking VC algorithms on the seven classic images including ED, probabilistic, our method, and random-grid. devices often have limited resources, making traditional image collection and protection strategies unsuitable. As a secret-sharing scheme for images, VC offers a lightweight security transmission solution that combines images and cryptography, with its threshold property ensuring that the encrypted image alone does not reveal any information about the original image.