## 4 Application Results and Discussion
** & **Depth/m** & **Dip/\({}^{\circ}\)** & **Dip Angle/\({}^{\circ}\)** & **Gap Width/mm** \\ \hline a1 & \(-0.618\) & \(155\) & \(44\) & \(9.1\) \\ a2 & \(-1.083\) & \(315\) & \(42\) & \(10.5\) \\ a3 & \(-1.782\) & \(100\) & \(46\) & \(8.3\) \\ a4 & \(-1.994\  
Since the manual interpretation results were repeatedly proofread, they can be taken as the correct standard data. As such, they were used as a reference point from which to statistically measure the effectiveness of automatic recognition. The standard of accurate recognition was defined as a deviation of less than 15% between the automatically identified structural plane parameters and the actual ones. Accordingly, the standard for \begin{table}
\begin{tabular}{c c c c c} \hline \hline
**No.** & **Depth/m** & **Dip/\({}^{\circ}\)** & **Dip Angle/\({}^{\circ}\)** & **Gap Width/mm** \\ \hline
1 & \(-\)0.616 & 154.6 & 44.37 & 8.57 \\
2 & \(-\)1.083 & 162.3 & 71.96 & 9.48 \\
3 & \(-\)1.083 & 315.1 & 41.59 & 10.66 \\
4 & \(-\)1.083 & 315.8 & 50.73 & 6.74 \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Fine recognition data for the structural planes in the borehole images shown in Figure 5. \begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**Type** & **Total Number** & **Right** & **Wrong** & **Missed** & **RMS (\%)** & **Time** \\ \hline
**Manual interpretation** & 217 & 217 & 0 & 0 & 0 & 7 days \\
**Automatic recognition** & 196 & 192 & 26 & 21 & 3.2 & 4 h \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Comparison between automatic recognition and manual reading for structural planes in the borehole images. Figure 7: Fine recognition results for Figure 3a. inaccurate recognition was defined as a deviation of not less than 15%. Four structural plane parameters were analyzed: structural plane position, dip direction, dip, and gap width. The recognition result is regarded as inaccurate if the deviation in any one of the four parameters is not less than 15%. Table 3 shows that, taking the manual interpretation result as the standard data, the recognition rate of the automatic recognition method was about 90.3%, the accuracy rate was about 88.5%, and the average deviation of the parameters of the accurate recognition results was about 3.2%. The time cost was reduced from seven days at normal manual working efficiency to about four hours of continuous computer operation. A closer look at the panoramic borehole image area to assess misjudgment and missing structural planes shows that these errors all occurred in damaged areas of rock mass structure. The structural plane fractures are very irregular and not obvious or without ambiguity. The imaging quality of the hole wall in the area where these misjudgments are located is also very poor. The manual interpretation of the fracture characteristics of rock mass structures is also controversial, and images need to be compared with drill cores to make a judgment. In addition, in image areas where the image quality of the hole wall is high and the structure surface is relatively clear, the automatic recognition technology was able to accurately identify all the structure planes and their characteristic parameters. The deviation between manual interpretation and automatic recognition was small. The technology described in this article is feasible and reliable for fully automatic identification of structural planes of panoramic borehole images and the intelligent extraction of related parameters. From the perspective of working hours and working methods, the automatic identification method can greatly improve work efficiency, from several days of manual work to a few hours of computer work, speeding up engineering progress, and saving workforce and material resources.