Aiming at the problem that the geometric features used for 3D point cloud registration, a combination of DAISY descriptor and LBP descriptor is used to extract the image features of the overlapping area of adjacent measurement stations, and the positions between the coordinate systems of adjacent measurement stations are solved. The transformation matrix is used to transform the 3D point cloud data of multiple measurement stations into the same coordinate system. First, the edge detection and the construction of DAISY descriptors are introduced. Then, the feature points of adjacent pictures are matched by Euclidean distance, and the coordinate transformation relationship at different stations is calculated based on the relationship between the matching points. The experimental results show that the method can well realize the coarse stitching of 3D point cloud data without using other auxiliary tools, and provide a theoretical basis for the application of point cloud registration technology in the fields of 3D reconstruction and reverse engineering.