## 3 Main Scheme
### Algorithm III. Meaningful Shares Scheme
The remaining shares will restore \(G_{2}\) in the same way. Similar to [8], restoring the \(i\)th secret

Figure 11: Process chart of Method 4 Steps 1-3. Figure 4:0 Experimental results by Method 4 for (5, 5) with \(p=45,\ \gamma=0.5\). (**a,b**) Restored images \(R_{0},R_{1}\) (**c–g**) Shares \(M_{0},\ldots,M_{4}\). Figure 4:1 Experimental results by Method 4 for (8, 8) with \(p=10,\ \gamma=0.5\). (**a–c**) Camouflage images \(D_{5},D_{6},D_{7}\), (**d,e**) Restored images \(R_{0},R_{1}\) (**f–m**) Shares \(M_{0},\ldots,M_{7}\). image requires shifting \(G_{2}\)'s \(iw/p\) pixels and stacking them on \(G_{1}\) by applying an XOR operation. We present Algorithm 7 for Algorithm IV as shown below. In Figure 14, the schematic is displayed. ## 4 Analysis

In this section, we perform some evaluations of the security and accuracy of the proposed schemes, and then analyze the experimental results of the proposed schemes. We discuss the contrast, PSNR, Sensitivity and SSIM, and security analysis for the proposed scheme in the following four subsections. Users can observe the changes of different methods under different values of \(\gamma\). ### Contrast Analysis

The security of a VCS and visual quality of restored images are important. We introduce the definition of _transmittance_ and _contrast_, and calculate the contrast for the proposed VCS in this subsection. Usually, the value of contrast is defined as \(\alpha\). The higher the contrast, the better the visual quality of the restored image. In a XOR-based VCS, the maximum possible contrast ratio is 1, which means perfect reconstruction--the restored image is exactly equal to the secret image. At first, we introduce the definition of the average transmittance. In the transmittance of an image \(S\), \(T(S)\) represents the proportion of white pixels in \(S\), that is \(T(S)=\) the number of white pixels in \(S\)/the total number of pixels in \(S\). Allow \(T[G[X(0)]]\) to stand for the average transmittance of the area in image \(G\) that corresponds to the white (transparent) area in image \(X\). The average transmittance of the area in image \(G\) that corresponds to the black (opaque) area in image \(X\) is indicated by the notation \(T[G[X(1)]]\). Under this definition, we can discuss the case where \(G=\) the restored image \(R\), \(X=\) the secret image \(S\), \(G=\) meaningful share \(M\), and \(X=\) camouflage image \(D\). As

Figure 4:2 The schematic diagram of Algorithm 7.

a result, the following formula can be used to determine the contrast of the restored image \(R\) and meaningful share \(M\). Figure 4:3

Figure 4:4

We utilize each of the seven images in Figure 5 as the secret and camouflage image in turn to get more precise results. That means in total 71 = 5040 experiments were performed. Let \(N\) = 2, \(n\) = 5, and \(p\) = 45. Table 2 shows the average results (from 5040 experiments) for the average contrast of five shares and restored two images of the proposed Methods 1-4 when \(\gamma\) is 1, 0.7, 0.5, 0.3, or 0. As \(\gamma\) decreases, the contrast value of the shares decreases while the contrast of the restored images increases, as seen in Figure 4:5 \(\alpha_{shares}\) in Methods 1-3 is almost the same and better than \(\alpha_{shares}\) in Method 4. The contrast of the two restored images is about the same when the value of \(\gamma\) is the same for Methods 1, 2, and 4. In the case of Method 3 with the same value of \(\gamma\), the contrast of the first restored image (almost 1) is much better than that of the second restored image. In conclusion, the average contrast of the restored images of Method 1 gives the best results. Method 3 has the best contrast of the first restored image, while the contrast of the second restored image is worse than that of the other methods.