## 3 Results and Discussion
For the two same images, the SSIM is one. An SSIM closer to one indicates less distortion from the cover image. \[SSIM=\frac{\left(2\times\overline{O}\times\overline{S}+C1\right)\times\left(2 \times\sigma_{OS}+C2\right)}{\left(\sigma_{O}^{2}+\sigma_{S}^{2}+C2\right) \times\left(\left(\overline{O}\right)^{2}+\left(\overline{S}\right)^{2}+C1 \right)} \tag{9}\]  
**Correlation:** Correlation (R) is given by Equation (10). For the two same images, the correlation is one. A correlation closer to one indicates less distortion from the cover image. \[AAD=\frac{\sum\limits_{i=1}^{M}\sum\limits_{j=1}^{N}(|O(i,j)-S(i,j)|)}{M\times N} \tag{2}\]0  
**Structural Content**: Structural Content (SC) is given by Equation (11). For the two same images, the SC is one. An SC closer to one indicates less distortion from the cover image. \[AAD=\frac{\sum\limits_{i=1}^{M}\sum\limits_{j=1}^{N}(|O(i,j)-S(i,j)|)}{M\times N} \tag{2}\]1  
These image quality parameters are evaluated for four cover images. The results of the proposed embedding algorithm are compared with the image quality parameters obtained from various familiar transform domain embedding techniques [25], such as Discrete Fourier Transform (DFT), Discrete Cosine Transform (DCT), Discrete Wavelet Transform (DWT), and Integer Wavelet Transform (IWT). The result for the single cover image (cover image1) is tabulated in \[AAD=\frac{\sum\limits_{i=1}^{M}\sum\limits_{j=1}^{N}(|O(i,j)-S(i,j)|)}{M\times N} \tag{2}\]2 It is observed that the proposed algorithm produces better results when compared to existing algorithms. The stego images are displayed on the display screen and captured using a camera. The specifications of the camera are given in \[AAD=\frac{\sum\limits_{i=1}^{M}\sum\limits_{j=1}^{N}(|O(i,j)-S(i,j)|)}{M\times N} \tag{2}\]3 A captured image with much less geometric distortion is considered as a reference image, as shown in Figure 13a. The captured image with geometric distortions is shown in Figure 13b. The Harris features are extracted from the both reference and captured images. The extracted features are matched for similarity, and the matching results are shown in Figure 13c. Out of all the matched features, only the features corresponding to the display screen are considered as valid features (Ref: Figure 13d). The geometric transform is estimated based on the valid features and applied for the captured image for restoration. The restored image is shown in Figure 13e. \begin{table}
\begin{tabular}{c c c c c c} \hline
**Parameter** & **IWT/ARC** & **IWT** & **DWT** & **DCT** & **DFT** \\ \hline AD & 0.0298 & 0.0312 & 0.0487 & 0.0692 & 0.0724 \\ AAD & 0.6843 & 0.7574 & 0.7728 & 0.7822 & 0.7218 \\ IF & 0.9942 & 0.9870 & 0.9870 & 0.9868 & 0.9765 \\ MSE & 0.4815 & 0.6155 & 0.6602 & 0.6596 & 0.7432 \\ RMSE & 0.6939 & 0.7845 & 0.8125 & 0.8122 & 0.8621 \\ PSNR & 51.3048 & 50.238 & 49.934 & 49.938 & 48.775 \\ NK & 0.9985 & 0.9971 & 0.9973 & 0.9969 & 0.9965 \\ BER & 0.0198 & 0.0287 & 0.0288 & 0.0288 & 0.0315 \\ SSIM & 0.9886 & 0.9816 & 0.9714 & 0.9715 & 0.9843 \\ R & 0.9997 & 0.9989 & 0.9989 & 0.9989 & 0.9989 \\ SC & 0.9915 & 0.9868 & 0.9860 & 0.9859 & 0.9824 \\ \hline \end{tabular}
\end{table} 
Table 2: Image analyses for cover image 1. \begin{table}
\begin{tabular}{c c} \hline
**Specification** & **Value** \\ \hline Resolution & 13 Mega Pixels \\ Frame Rate & 30 Frames per second \\ Width of the captured image & 4160 pixels \\ Height of the captured image & 3120 pixels \\ \hline \end{tabular}
\end{table} 
Table 3: Camera Specifications. A Hough transform is applied to the restored image and lines are detected in the restored image, as shown in Figure 14. Only vertical and horizontal lines having line distance equivalent to the border of the display screen are selected by restricting the theta values to 0 \(\pm\) 5\({}^{\circ}\) and 90 \(\pm\) 5\({}^{\circ}\) respectively. The selected lines are used to extract the received stego image, as shown in Figure 15a-d.