Abstract: Euclidean clustering algorithm is an important classification method of multivariate statistical analysis. It can be applied to the segmentation of point cloud in survey field. Euclidean clustering algorithm firstly calculates the Euclidean distance between two points. The points' distance which are less than a specified threshold are divided into a kind. Until all kinds of distance are greater than the specified threshold, it completes Euclidean clustering segmentation. Specific steps are as follows:① using Octree method set up topology structure of point cloud data; ② for each point conduct K-nearest neighbor search, calculating the Euclidean distance between point and K neighboring points, the minimum is regard as one kind; ③ set a certain threshold, the iterative calculation ② steps until all distances between the classes are greater than the specified threshold. Experiments show that Euclidean clustering algorithm is available to point cloud data obtained from different measuring means. It can successfuly segment point cloud data and the effect is good.

Key words: Euclidean clustering, point cloud data, segmentation, algorithm