Abstract: The structural surfaces in the surrounding rock of tunnels are one of the main factors affecting the stability of the surrounding rock. Traditional methods for obtaining these structural surfaces have shortcomings such as low work efficiency, large workload, and strong subjectivity. To address issues like the reconstruction of real-world tunnel surrounding rock models, 3D point cloud extraction, and structural surface recognition, a self-lighting digital image acquisition device for underground tunnel chamber surrounding rock has been developed to improve the quality of tunnel surrounding rock image collection. Using the SFM algorithm, a 3D real-world model of the tunnel surrounding rock is reconstructed, and point cloud data is extracted. An algorithm has also been developed to identify rock mass structural surfaces based on the normal vector features of the tunnel surrounding rock point cloud. A semi-automated identification system for tunnel surrounding rock structural surfaces has been developed. Taking a specific tunnel as an example, the practical application of technologies such as digital image acquisition, 3D real-world model reconstruction, and point cloud information extraction has been carried out. The developed system has been used to identify the structural surfaces of the tunnel surrounding rock, and the research findings have certain reference value..