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Point cloud registration based on the 4PCS+ICP algorithm will lead to many problems such as large registration error, low efficiency, and unstable running time, especially when it encounters large point cloud data, these problems will be more prominent, which greatly limits the application of the algorithm. Based on these shortcomings, we propose an optimized registration algorithm, called BH4PCS, to improve the applicability of the 4PCS algorithm. In our method, we first extract the boundary Harris-3D points through the edge detection algorithm and Harris-3D key point extraction method, then we use the 4PCS algorithm for point cloud coarse registration, and finally use KD-ICP to speed up the fine registration. After experimental verification and comparison with the existing artworks, our proposed algorithm registers the larger point cloud model by only using a small number of data points, optimizing the registration efficiency, accuracy, and operation stability of the 4PCS + ICP registration method, and has good robustness to outliers.

Research on Point Cloud Registration Algorithm Based on Boundary Harris-3D Points and 4PCS