Research on the Method of Feature Extraction in Subway Tunnels Based on Three-dimensional Laser Point Clouds
In view of the structural characteristics of subway tunnels,in order to realize automated inspection of tracks and platform planes,this paper proposes a rapid extraction method of track and plane point cloud features based on geometric constraints.First,for the tunnel laser point cloud,the direction of the main axis of the point cloud is determined through PCA estimation and corrected to the level;on this basis,straight-through filtering is used to extract the tunnel cross-section point cloud,and the cross-section mathemat-ical model is constructed through RANSAC fitting;secondly,it calculates the distance from each plane point on the section to the cen-ter of the fitting circle,and extracts candidate orbit points and plane points based on the change in point-center distance;finally,it optimizes and solves the straight line and plane equations based on the characteristic points of the two groups of sections,calculates the point-line and point-surface distances to complete the straight line and planar feature extraction.The research results indicate that the orbit detection accuracy is good and the detection accuracy is high.
subway tunnelslaser point cloudsfeature extraction
万方数据
维普
