Planar Segmentation Using Range Images From Terrestrial Laser Scanning

Various methods are available for the planar segmentation of point clouds from terrestrial laser scanning. In this letter, a new method is proposed to extract planar features from the range image of a point cloud scanned from one standpoint. In this method, a plane is parameterized by its normal vector and the distance from the origin. The algebraic derivation of the parameters is presented in this letter. The parameters are calculated based on the gradient value of a pixel in the range image. The multiple-band synthetic image of planar parameters is segmented using the Iso cluster unsupervised classification method. Experimental plane segmentation results using range images of two point clouds are illustrated. In comparison with existing methods, the proposed method gives an exact estimation of the planar parameters and can handle planes of any orientation.