# WMNet: A Lossless Watermarking Technique Using Deep Learning for Medical Image Authentication
## 4 Experimental Results

Table 2: Results of 5-fold cross validation. after an image-processing attack. In addition, the NC of extracted watermarks all showed that lossless image watermarking systems have varying degrees of resilience, primarily because the core methods used by each technology are different, requiring the process to be adapted to resist damage from different types of image-processing attacks. However, even if the extracted watermark is distorted, WMNet can interpret whether the copyright information in the watermark is correct. Note that the watermark size is \(64\times 64\) when WMNet is constructed. When watermarks of different sizes are verified, the watermarks need to be resized to \(64\times 64\) before being interpreted by WMNet. Here, double linear interpolation is used to adjust the watermark size. Even after resizing, WMNet can clearly determine whether the copyright information in the watermark is correct. The above-mentioned experimental results demonstrate that WMNet, as proposed in this study, is effective. Even if the protected image is subjected to different types of image processing attacks, which cause the watermark to produce different distortion conditions, WMNet can be used to interpret watermark information for all watermarks extracted, regardless of the extraction method. This shows that WMNet is relatively flexible and can be used with different watermarking systems. It can improve the verification of the watermarking mechanism of a system for data security without changing the original system. The interpretation of the copyright information in the watermark is more accurate and objective. \begin{table}
\begin{tabular}{c c c c c c c c c c c c c c c} \hline \hline \multirow{2}{*}{**Attack**} & \multicolumn{8}{c}{**Wang’s Method [14]**} & \multicolumn{8}{c}{**Wu’s Method [18]**} \\ \cline{2-13}  & \multicolumn{4}{c}{**CT**} & \multicolumn{2}{c}{**X-ray**} & \multicolumn{2}{c}{**CT**} & \multicolumn{2}{c}{**X-ray**} & \multicolumn{2}{c}{**CT**} & \multicolumn{2}{c}{**X-ray**} \\  & **NC** & **1** & **W1** & **NC** & **2** & **W2** & **NC** & **W1** & **NC** & **W2** & **NC** & **W1** & **NC** & **W2** & **NC** & **W1** & **NC** & **W2** \\ \hline JPEG Compression & 0.99 & Y & 0.99 & Y & 0.99 & Y & 0.99 & Y & 0.99 & Y & 0.99 & Y & 0.99 & Y & 1 & Y \\ \hline JPEG 2000 & 0.98 & Y & 0.98 & Y & 0.99 & Y & 1 & Y & 1 & Y & 1 & Y & 1 & Y & 1 & Y \\ \hline Gaussian Noise & \multirow{2}{*}{0.95} & \multirow{2}{*}{Y} & \multirow{2}{*}{0.95} & \multirow{2}{*}{Y} & \multirow{2}{*}{0.98} & \multirow{2}{*}{Y} & \multirow{2}{*}{0.98} & \multirow{2}{*}{Y} & \multirow{2}{*}{0.98} & \multirow{2}{*}{Y} & \multirow{2}{*}{0.92} & \multirow{2}{*}{Y} & \multirow{2}{*}{0.93} & \multirow{2}{*}{Y} & \multirow{2}{*}{0.95} & \multirow{2}{*}{Y} & \multirow{2}{*}{0.95} & \multirow{2}{*}{Y} \\ Addition & & & & & & & & & & & & & & & & \\ \hline Salt-pepper Noise & \multirow{2}{*}{0.93} & \multirow{2}{*}{Y} & \multirow{2}{*}{0.96} & \multirow{2}{*}{Y} & \multirow{2}{*}{0.98} & \multirow{2}{*}{Y} & \multirow{2}{*}{0.99} & \multirow{2}{*}{Y} & \multirow{2}{*}{0.94} & \multirow{2}{*}{Y} & \multirow{2}{*}{0.93} & \multirow{2}{*}{Y} & \multirow{2}{*}{0.95} & \multirow{2}{*}{Y} & \multirow{2}{*}{0.96} & \multirow{2}{*}{Y} \\ Addition & & & & & & & & & & & & & & & & \\ \hline Median Filtering & 0.97 & Y & 0.98 & Y & 1 & Y & 0.99 & Y & 0.99 & Y & 0.99 & Y & 1 & Y & 0.99 & Y \\ \hline Rotation & 0.94 & Y & 0.92 & Y & 0.95 & Y & 0.93 & Y & 0.97 & Y & 0.97 & Y & 0.93 & Y & 0.94 & Y \\ \hline Cropping & 0.93 & Y & 0.94 & Y & 0.92 & Y & 0.92 & Y & 0.94 & Y & 0.94 & Y & 0.91 & Y & 0.92 & Y \\ \hline Scaling & 0.97 & Y & 0.96 & Y & 0.99 & Y & 0.99 & Y & 0.99 & Y & 0.99 & Y & 0.98 & Y & 0.99 & Y \\ \hline \hline \end{tabular}  
* \({}^{1}\) W1: Results for \(64\times 64\) watermark; \({}^{2}\) W2: results for \(32\times 32\) watermark; \({}^{m}\)Y\({}^{m}\) indicates the extracted watermark is interpreted correctly by WMNet; \({}^{m}\)N\({}^{m}\) indicates the extracted watermark is interpreted incorrectly by WMNet.  
\end{table}