The compression of point cloud is one step of the necessary preprocessing in the reverse engineering modeling. The issue of detection and preservation of boundary points

however

has not been usually considered in many point cloud compression algorithms. Then

boundary points could be withdrawn during large scale compression

and integrality of data could not be guaranteed. In this paper

we provide an algorithm to detect the boundary points. Obviously

if a point is a boundary point

then its circumambient points will distribute only on one side or around a corner. If a point is not a boundary point

its neighboring points will distribute symmetrically. By this way

boundary points will be detected by analyzing the relation of points in a trivial neighboring region. The algorithm will be effective for inner boundary points as well as outers. It sorts the boundary points further

and detects the transitional points in boundary points

at last constructs boundary polygon lines by transitional points. The distance between a boundary point and its neighboring boundary points is used to detect the transitional points. Therefore

the algorithm not only can satisfy preserving the boundary points in a large scale compression

but also prepare for reversion modeling by boundary polygon lines.