# Table Recognition for Sensitive Data Perception in an IoT Vision Environment
## 4 Experiments and Analysis
### Error Type Analysis  
The obvious cases of trapezoid and quadrilateral are used to analyze the error types occurring in our method, because these perspective transformation cases are most common. There are 45 tables in every case in this experiment with 1250 table cells of entry fields and 483 table cells of fixed fields. Tables 3 and 4 show the error types of our method, [PERSON]'s method, and [PERSON]'s method in trapezoid and quadrilateral, respectively. From the total number of error table cells, there is a lower error table-cell number in our method compared with other methods, no matter whether in the case of trapezoid or quadrilateral. Furthermore, in every error type, the error number of our method is also less than [PERSON]'s method, except for split error, which implies our method will have more split error, which is because text or stamp interference is not filtered completely by the short DCC removal and abnormal DCC removal, or the short DCC is extended so long in the DCC extension step that table cells are split. However, there is less split error in our method compared to [PERSON]'s, because [PERSON]'s method will merge the DSCCs when their added length is close to the table cell's. In addition, [PERSON]'s method has more miss error than our method, because the strict DSCC search algorithm causes more breakage. The above two points are the reasons for the low accuracy of [PERSON]'s method. The miss error and merge error are more frequent in our method, which implies that the removal techniques, such as abnormal DCC remove and short DCC removal, filter excessively. Meanwhile, there is no fault error in our method, which implies the outermost frame of the table is exactly determined.  
\begin{table}
\begin{tabular}{c c c c c c c c c c c} \hline \hline \multirow{2}{*}{**Method**} & \multicolumn{4}{c}{**Entry Fields**} & \multicolumn{4}{c}{**Fixed Fields**} \\ \cline{2-11}  & **Miss** & **Fault** & **Merge** & **Split** & **Total** & **Miss** & **Fault** & **Merge** & **Split** & **Total** \\ \hline Our method & 41 & 0 & 36 & 8 & 85 & 5 & 0 & 14 & 7 & 26 \\ [PERSON]’s method & 257 & 0 & 5 & 0 & 262 & 58 & 0 & 7 & 0 & 65 \\ [PERSON]’s method & 126 & 0 & 31 & 41 & 198 & 37 & 0 & 3 & 19 & 59 \\ \hline \hline \end{tabular}
\end{table}
Table 4: Numbers of every Error types in obvious case of quadrilateral.  
\begin{table}
\begin{tabular}{c c c c c c c c c c c} \hline \hline \multirow{2}{*}{**Method**} & \multicolumn{4}{c}{**Rotation**} & \multicolumn{4}{c}{**Trapezoid**} & \multicolumn{4}{c}{**Quadrangle**} \\ \cline{2-11}  & **Slight** & **Obvious** & **Serious** & **Slight** & **Obvious** & **Serious** & **Slight** & **Obvious** & **Serious** \\ \hline Our method & 94.84\% & 96.51\% & 92.46\% & 94.42\% & 93.66\% & 79.62\% & 94.41\% & 93.66\% & 84.11\% \\ [PERSON]’s method & 89.22\% & 28.38\% & 5.60\% & 81.12\% & 84.91\% & 70.74\% & 92.73\% & 78.50\% & 69.34\% \\ [PERSON]’s method & 84.94\% & 82.65\% & 68.90\% & 81.86\% & 77.93\% & 62.98\% & 83.39\% & 78.21\% & 70.00\% \\ \hline \hline \end{tabular}
\end{table}
Table 2: Accuracy of various perspective transformation.  
\begin{table}
\begin{tabular}{c c c c c c c c c c c} \hline \hline \multirow{2}{*}{**Method**} & \multicolumn{4}{c}{**Entry Fields**} & \multicolumn{4}{c}{**Fixed Fields**} \\ \cline{2-11}  & **Miss** & **Fault** & **Merge** & **Split** & **Total** & **Miss** & **Fault** & **Merge** & **Split** & **Total** \\ \hline Our method & 15 & 0 & 23 & 14 & 52 & 14 & 0 & 4 & 1 & 19 \\ [PERSON]’s method & 60 & 0 & 10 & 0 & 70 & 30 & 0 & 5 & 0 & 35 \\ [PERSON]’s method & 110 & 0 & 29 & 50 & 189 & 37 & 0 & 3 & 19 & 59 \\ \hline \hline \end{tabular}
\end{table}
Table 3: Numbers of every Error types in obvious case of trapezoid.