Abstract: A new spherical target recognition method based on mutual exclusion of sphere centers is
proposed to solve the automatically identification problems of unknown number and unknown radius
targets in large-scale 3D point clouds. First, an effective spherical point response function is specially
designed to remove most of aspheric points, and every remaining spherical point is mapped to a
sphere center by taking advantage of its normal and curvatures. Then, a novel tree-like structure for
describing distribution and local density change rules of these centers is constructed, through a series
of pruning operation complying with the mutually exclusion relationships between different sphere
centers, the tree is split into several sub-trees, and a sub-tree correspond to a possible sphere target.
Finally, the real sphere is confirmed by the local density of the root node of sub-tree and the coverage
rate of points on the sphere surface. The experimental results demonstrate that the proposed sphere
recognition method based on the mutual exclusion of sphere centers can effectively identify and
precisely loc ate various spherical targets in a large and cluttered scene. Even in the case of serious
occlusion, such as the exposed surface is less than 6%, the sphere can also be robustly identified.

Key words: spherical target recognition, spherical point response function, spherical center mutual exclusion, clustering, spherical coverage