A Curvature-based Automatic Registration Algorithm for the Scattered Points

An automatic registration algorithm for the scattered point clouds is proposed in this paper. The curvature of each point is estimated by using the quadratic surface fitting method. And then, according to the change of curvature the feature points that have the maximum local changes are extracted. The initial match points are acquired by computing the Hausdorff distance of curvature, and the feature of the surface circumference shape is used on the initial match points to obtain the accurate match points. Finally, the rotation and translation matrix are estimated by the quaternion, and iterative solution is used to improve the registration accuracy. So, the automatic match of the scattered point cloud data is completed. Experimental results show that the algorithm is effective.