A subway tunnel image stitching method based on point cloud mapping relationships and high-resolution image

Abstract The paper presents an intelligent tunnel 3D laser image acquisition system. The system can quickly acquire the 3D point cloud and tunnel surface image of the whole tunnel section. The paper proposes the subway tunnel image stitching method based on point cloud mapping relationships and high-resolution image. Firstly, the method extracts the homonymous points from the mapped image generated from the 3D point cloud and the camera image based on the maximum information coefficient method. Secondly, the 3D point cloud positions corresponding to the homonymous points are determined. The optimization of camera parameters is achieved based on the gradient descent method. Then, the tunnel point cloud is expanded to generate a gray scale image based on spherical projection. Based on the optimized parameters, the point cloud is projected to the camera image to determine the depth value of each camera image pixel point. Finally, the pixel values of the camera image are projected based on the spherical projection to obtain the stitching result images. This method stitches individual images together to form a more complete tunnel surface image. The larger tunnel surface image helps in identifying tunnel defects.