## 5 Conclusions  
The authors used the DPBCS to perform borehole imaging of eight borehole walls in the dam site area of Wudongde Hydropower Station and the Jinpingzi landslide area of the hydropower station, and to obtain data from the panoramic borehole image of each hole. In the obtained borehole video image data, an automatic recognition method based on cluster projection and feature function matching was used to identify features from each panoramic borehole image and practical engineering application automatically. The engineering application results show that the automatic recognition technology can comprehensively and quickly identify most of the structural planes and their position, dip, dip direction, and gap width from full-hole panoramic borehole images. Furthermore, preliminary classification of the parameters of the structural planes was performed and the results were statistically analyzed. As a result, the following conclusions can be made:  
1. In practical engineering, the automatic recognition method based on cluster projection and feature function matching can automatically identify the structural planes in a full-hole panoramic borehole image. Furthermore, it can extract the position, dip, dip direction, and gap of structural planes, and perform annotation and statistical analysis.
2. When used on the panoramic borehole images from Wudongde Hydropower Station, the recognition rate of this automatic recognition method was approximately 90.3%, the accuracy rate was approximately 88.5%, and the average deviation of the parameters of the accurate recognition results was approximately 3.2%. Thus, the efficiency was much greater compared to manual interpretation.
3. The application of automatic recognition technology to panoramic borehole images in engineering practice greatly improved efficiency. The working time was reduced from the original seven days to about four h, which shortened the engineering time cost and provided a timely and effective data analysis result. The technology also contributes to the further intellectualization of borehole imaging.
4. In complex or poorly imaged structural surface areas, especially in the crushing zone of a rock mass, the automatic recognition method inevitably returns some erroneous or inaccurate recognition results. In order to ensure the quality of the practical project and the authenticity and reliability of the structural plane data, it is recommended to use the automatic identification method to reach a preliminary result, and then use the fine identification method and manual interpretation to identify the structural plane data compared to the original panoramic borehole images. If necessary, the data can be manually modified to ensure the authenticity of the final structural plane data.  
Conceptualization, X.Z. and C.W.; methodology, X.Z.; software, X.Z.; validation, X.Z. and H.Z.; formal analysis, X.Z.; investigation, S.C.; resources, X.Z.; data curation, X.Z.; writing--original draft preparation, S.C.; writing--review and editing, X.Z.; visualization, X.Z.; supervision, C.W.; project administration, X.Z.; funding acquisition, X.Z. All authors have read and agreed to the published version of the manuscript.  
This research was funded by the National Natural Science Foundation of China (42007266) and the Natural Science Foundation of Hubei Province (2019 CFB345).  
Not applicable.  
All data, models, and code generated or used during the study appear in the submitted article.  
All the images and data are from our actual tests and permitted by the owners. We are compliant with ethical standards, and all authors declare that this paper has no conflict of interest. Finally, we are grateful for the many helpful and constructive comments from many anonymous reviewers.  
The authors declare no conflict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, or in the decision to publish the results.