In view of the spatial feature correlation of adjacent station clouds collected by ground three-dimensional laser scanners, and a large number of line-planar features in urban buildings, a point cloud registration method based on line-planar feature constraints described by dual quaternion is proposed. This method not only uses dual quaternion to describe spatial transformation parameters, but also takes into account the scale factor. The objective function of spatial similarity transformation is constructed according to the geometric relationship between line-planar, as well as the intersection point and angle caused by the intersection of line-planar as registration constraints. The adjustment model is constructed by using the least square criterion to calculate the relevant parameters of spatial similarity transformation. In order to avoid the problem of iterative non-convergence caused by inappropriate initial values, the Levenberg-Marquardt method is applied to the solution of the adjustment model. Finally, the correctness and feasibility of the method are analyzed by experiments. The results show that the registration accuracy of the proposed method is higher than that of the point cloud registration method considering only linear of planar feature constraints, and the adjustment model solved by Levenberg-Marquardt method can converge correctly under any given initial value.