A profound research reveals the defects of the existing point cloud segmentation and fitting algorithms.The paper presents new algorithms according to the intrinsic characteristics of scanned line data.Random sample consensus(RANSAC) algorithm is modified,and a more robust and efficient algorithm is obtained with the better extraction result and more rational segmentation result.A weight determining algorithm for ends of fitted line segments used in plane fitting is proposed, which solves the problem in traditional algorithms that ends of line segments can′t be used in plane fitting directly because of the different weights.Besides,a set of integral invalid plane removing algorithm is proposed. A case study show that better plane extraction results of point cloud are achieved with the proposed algorithm.
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PAN Guorong, QIN Shiwei, CAI Runbin, GU Chuan. Fitted Plane Automatic Extraction Algorithm of 3-D Laser Scanning[J].同济大学学报(自然科学版),2009,37(9):