Geological logging of tunnel surrounding rock based on multi-view geometry and image stitching

Geological logging of tunnel surrounding rock based on multi-view geometry and image stitching

Zhuang Xie Zhiheng Zhu  Jinyang Fu  Junsheng Yang  Bin Peng 

School of Civil Engineering, Central South University, Changsha 410075, China

Hunan Electric Power Design Institute Co., Ltd., Changsha 410007, China

MOE Key laboratary of Engineering Structures of Heavy Haul Railway, Changsha 410075, China

Corresponding Author Email:
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The geological map of tunnel surrounding rock is essential to the design of dynamic construction and the stability analysis and reinforcement of rock mass. Based on computer vision technology, this paper proposes a fast and flexible method for preparing geological maps of tunnel surrounding rock. By this method, the 3D point cloud of the target tunnel was reconstructed from multiple photos using the multi-view geometry principles; then, the orthographic projection model of the tunnel was determined from the spatial point cloud through 3D surface estimation; after that, each photo on surrounding rock was subjected to geometric correction based on the relative position between cameras and orthographic projection model; finally, the orthographic display maps of the chamber wall and tunnel face were obtained by stitching the corrected photos. The image processing software inspired by this method can automatically generate the geological map on the tunnel surrounding rock in each work cycle based on the set of photos shot freely from multiple angles. Through engineering application, it is proved that the proposed method outperforms the existing tunnel geological logging methods in terms of the flexibility and efficiency of field shooting, as well as the universality and intuitiveness of the automatically generated geological maps on tunnel surrounding rock. The research findings provide an intuitive reference for tunnel construction design and boast profound significance in engineering application.


tunnel construction, computer vision, photographic geological logging

1. Introduction
2. Field shooting of tunnel excavation face
3. 3D point cloud reconstruction of tunnel excavation face
4. Construction and identification of orthographic projection model of tunnel excavation face
5. Geometric correction and stitching of photos
6. Conclusions

This work is supported by Project of National Key R & D Plan (No.2016YFC0802504); Project of National Natural Science Foundation of China (No.51608539); Project of China Postdoctoral Science Foundation (No.2016M592451, No. 2017T100610); Science and Technology Project of Guizhou Provincial Transportation Department (No.2018-133-042, No.2018-123-040).


Agarwal S., Snavely N., Seitz S. M., Szeliski R. (2010). Bundle adjustment in the large. Computer Vision–ECCV 2010, pp. 29-42.

Bay H., Ess A., Tuytelaars T., Gool L. V. (2008). Speeded-up robust features (SURF). Computer Vision and Image Understanding, Vol. 110, No. 3, pp. 346-359.

Besl P. J., McKay N. D. (1992). A method for registration of 3-D shapes. IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 14, No. 2, pp. 239-256.

Brown M., Lowe D. G. (2007). Automatic panoramic image stitching using invariant features. International Journal of Computer Vision, Vol. 74, No. 1, pp. 59-73.

Buyer A, Schubert W. Calculation the spacing of discontinuities from 3D point clouds. Procedia Engineering, Vol. 191, pp. 270-278.

Chaiyasarn K., Kim T. K., Viola F., Cipolla R., Soga K, (2015). Distortion-free image mosaicing for tunnel inspection based on robust cylindrical surface estimation through structure from motion. Journal of Computing in Civil Engineering, pp. 04015045.

Chen X. X., Li H., Zhang M. Q. (2005). The comparison of two distortion calibration model for general digital camera. Beijing Surveying and Mapping, No. 4, pp. 50-54.

Fischler M. A., Bolles R. C. (1981). Random sample consensus: A paradigm for model fitting with applicationsto image analysis and automated cartography. Communications of The ACM, Vol. 24, No. 6, pp. 381-395.

Hartley R., Zisserman A. (2004). Multiple view geometry in computer vision. Cambridge, UK: Cambridge University Press, pp. 239-259.

Heymsfield E., Kuss M. L. (2013). Implementing gigapixel technology in highway bridge inspections. Journal of Performance of Constructed Facilities, Vol. 29, No. 3, pp. 04014074.

Leng B. (2009). Research of tunne1 face geo1ogy information system based on digital image. Southwest Jiaotong University, pp. 25-31.

Li H., Zhang R. C., Yang B., Wu M. F. (2014). Principle and geometric precision of photo geological logging for tunnel. Journal of Applied Remote Sensing, Vol. 8, No. 1, pp. 083617.

Li H., Zhang Y. J., Hua X. S., Yang B. (2004). Geologic logging of digital photos and its basic algorithm. Editorial Board of Geomatics and Information Science of Wuhan University, Vol. 29, No. 9, pp. 805-808.

Li S. C., Liu H. L., Li L. P., Shi S. S., Zhang Q. Q., Sun S. Q., Hu J. (2017). A quantitative method for rock structure at working faces of tunnels based on digital images and its application. Chinese Journal of Geotechnical Engineering, Vol. 36, No. 1, pp. 1-9.

Lowe D. G. (2004). Distinctive image features from scale-invariant keypoints. International Journal of Computer Vision, Vol. 60, No. 2, pp. 91-110.

Nocedal J., Wright S. J. (2006). Numerical optimization. Springer Series in Operations Research and Financial Engineering, pp. 262-266.

Papazov C., Burschka D. (2011). An efficient RANSAC for 3D object recognition in noisy and occluded scenes. computer vision – ACCV 2010, pp. 135-148. 10.1007/978-3-642-19315-6_11

Rusinkiewicz S., Levoy M. (2002). Efficient variants of the ICP algorithm. Proceedings Third International Conference on 3-D Digital Imaging and Modeling, pp. 145.

Snavely N., Seitz S. M., Szeliski R. (2006). Photo tourism: Exploring photo collections in 3D. Acm Transactions on Graphics, Vol. 25, No. 3, pp. 835-846.

Snavely N., Seitz S. M., Szeliski R. (2007). Modeling the world from internet photo collections. International Journal of Computer Vision, Vol. 80, No. 2, pp. 189-210.

Song Y., Wang X., Li Y., Li R. (2013). Contrast research on application of 3-dimensional laser scanning technology and digital imaging geology catalog system in acquisition of rock mass information of tunnels. Tunnel Construction, Vol. 3, No. 3, pp. 197-202.

Szeliski R. (2004). Image alignment and stitching: A tutorial, microsoft research. Faugeras (eds), Handbook of Mathematical Models in Computer Vision, Vol. 2, No. 11-12, pp. 273-292.

Szeliski R. (2010). Computer vision: Algorithms and applications. Springer-Verlag New York, Inc., pp. 812.

Wang M. H. (2007). Key techniques of geologic logging information system for complex tunnel. HoHai University, pp. 1-3.

Wang M. H., Li H., Cang G. H. (2007). Application of ordinary digital cameras in tunnel logging. Coal Geology & Exploration, Vol. 4, pp. 15-19.

Wang Y., Wang S. H., Guo M. D., Dong Z. H. (2011). Fast digital identification of joint information of tunnel work face and its stability analysis. Chinese Journal of Geotechnical Engineering, No. 11, pp. 1734-1739.

Winkelbach S., Molkenstruck S., Wahl F. M. (2006). Low-cost laser range scanner and fast surface registration approach. Pattern Recognition, pp. 718-728.

Wu C. C. (2013). Towards linear-time incremental structure from motion. 2013 International Conference on 3D Vision - 3DV 2013, pp. 127-134.

Yan J. G., Gao G. P. (2007). Application study of geological mapping technique for underground cavern surrounding rock. Technical Supervision in Water Resources, No. 3, pp. 27-30.

Yang C. H., Li H., Yang L. (2003). The development of measurable digital camera. Engineering of Surveying and Mapping, Vol. 12, No. 2, pp. 34-37.

Yang C. H., Song H. J., Chen C. M. (2001). Digital image processing in photographic geological recording system. Modern Surveying and Mapping, Vol. 24, No. 3, pp. 15-18.

Yang L., Li H. (2002). Digital image projection algorithm and its application in geological catalog. Modern Surveying and Mapping, No. 4, pp. 30-33.

Yang L., Li H., Lv G. N. (2004). A method for digital camera calibration. Bulletin of Surveying and Mapping, No. 8, pp. 50-52.

Zhang Y. H., Li L. P., Liu H. L., Yang W. M., Shi S. S. (2016). Digital identification of evaluation of tunnel surrounding rocks discontinuity. Tunnel Construction, Vol. 36, No. 12, pp. 1471-1477.

Zhou C. L., Zhu H. H., Li X. J. (2008). Application of infrared photography and image processing to tunnel construction with new austrian tunneling method. Chinese Journal of Rock Mechanics and Engineering, Vol. 27, No. S1, pp. 3166-3172.

Zhu Z. H., Yang J. S., Xiao C., Liu Q. T. (2014). A method for tunnel lining surface photo flattening based on shape functions transform. Journal of Railway Science and Engineering, No. 3, pp. 101-106.

Zhu Z., Fu J. Y., Yang J., Yang J. S. (2016). Panoramic image stitching for arbitrarily shaped tunnel lining inspection. Computer-Aided Civil and Infrastructure Engineering, Vol. 31, No. 12, pp. 936-953.

Zhu Z., German S., Brilakis I. (2010). Detection of large-scale concrete columns for automated bridge inspection. Automation in Construction, Vol. 19, No. 8, pp. 1047-1055.