Abstract: In order to improve the efficiency of calculating the Hausdorff distance(HD distance)between point clouds,this paper presents an efficient Hausdorff distance calculation algorithm based on Z-Order and octree.First,the point sets are preprocessed in a structured format by Z-Order and octree partition.Then,two kinds of neighbor information are defined as neighborhood and neighbor-node.With a leaf node recorded as the start position,the algorithm searches its neighbors recursively until the root node.Combined with the idea of data preprocessing and local search,the implementation details of the algorithm are given.A set of experiments have been conducted against classical algorithms on 3D stochastic Gaussian data and the point clouds.The results demonstrate the presented algorithm is high-efficiency.