Occlusion Detection with Edge Extraction Algorithm in Terrestrial Laser Scanner Point Cloud Data

When the beam of a laser scanner because of an obstacle (such as trees or walls of a building) is not able to pass the complication, the points are on the backside, not measured. These points appear as occlusion parts of the point cloud that study of them is a key issue for the next station selection. Nowadays, occlusion area analysis study manually that this work is time-consuming and erroneous. In this paper new technique provide, which is used to determined occlusions of the laser scanner data, automatically. As we know, the edges in an image showing the drastic difference between adjacent pixels values. In the range image, the difference is due to the difference in depth in the presence of occlusions; its value will be high. Therefore, in this article to determine the occlusion borders automatically, made an image from the data collected by laser scanners and edges are extracted. After that, the borders defined on a reference plane and are connected to each other up to specified occlusion area. To implement this, the ground laser scanner station point cloud was used in an urban area. Canny technique was used to extract edges. The findings show that the proposed method can be used in the absence of complicating factors (such as trees) and occlusions of point cloud automatically can be identified.