Acta Geodaetica et Cartographica Sinica >

2015 , Vol. 44 >Issue 6: 655 - 662

DOI: https://doi.org/10.11947/j.AGCS.2015.20130208

Spherical Projection Based Straight Line Segment Extraction for Single Station Terrestrial Laser Point Cloud

  • ZHANG Fan ,
  • GAO Yunlong ,
  • HUANG Xianfeng ,
  • YIN Ruojie ,
  • ZHANG Zhichao ,
  • ZHU Yixuan
Expand
  • 1. State Key Laboratory of Information Engineering on Survey, Mapping and Remote Sensing, Wuhan University, Wuhan 430079, China;
    2. School of Remote Sensing and Information Engineering, Wuhan University, Wuhan 430079, China

Received date: 2013-06-07

  Revised date: 2014-09-25

  Online published: 2015-07-28

Supported by

The National Basic Research Program of China(973 Program)(Nos. 2012CB725300;2011CB707001);The National Key Technology Research and Development Program of the Ministry of Science and Technology of China (No. 2014BAK07B04);The National Natural Science Foundation of China (Nos. 41001308;41071291)

Fold

Abstract

Due to the discrete distribution computing errors and lack of adaptability are ubiquitous in the current straight line extraction for TLS data methods. A 3D straight line segment extraction method is proposed based on spherical projection for single station terrestrial laser point clouds. Firstly, horizontal and vertical angles of each laser point are calculated by means of spherical coordinates, intensity panoramic image according to the two angles is generated. Secondly, edges which include straight line features are detected from intensity panoramic image by using of edge detection algorithm. Thirdly, great circles are detected from edges of panoramic image using spherical Hough transform. According to the axiom that a straight line segment in 3D space is a spherical great circle after spherical projection, detecting great circles from spherical projected data sets is essentially detecting straight line segments from 3D data sets without spherical projection. Finally, a robust 3D straight line fitting method is employed to fitting the straight lines and calculating parameters of the straight line segments. Experiments using different data sets and comparison with other methods show the accuracy and applicability of the proposed method.

Key words： terrestrial laser scanning; straight line segment extraction; spherical projection; Hough transform

Cite this article

ZHANG Fan , GAO Yunlong , HUANG Xianfeng , YIN Ruojie , ZHANG Zhichao , ZHU Yixuan . Spherical Projection Based Straight Line Segment Extraction for Single Station Terrestrial Laser Point Cloud[J]. Acta Geodaetica et Cartographica Sinica, 2015 , 44(6) : 655 -662 . DOI: 10.11947/j.AGCS.2015.20130208

References

[1] WEN Gongjian, WANG Runsheng. A Robust Approach to Extracting Straight Lines[J]. Journal of Software, 2001, 12(11): 1660-1666. (文贡坚, 王润生. 一种稳健的直线提取算法[J]. 软件学报, 2001, 12(11): 1660-1666.)
[2] HABIB A, GHANMA M, MORGAN M, et al. Photogrammetric and LiDAR Data Registration Using Linear Features[J]. Photogrammetric Engineering and Remote Sensing, 2005, 71(6): 699-707.
[3] HUANG Xianfeng. Research on 3D Building Model Extraction from Airborne LIDAR Data[D]. Wuhan: Wuhan University, 2006. (黄先锋. 利用机载LIDAR数据重建3D建筑物模型的关键技术研究[D]. 武汉: 武汉大学, 2006.)
[4] DANIELS J, HA L K, OCHOTTA T, et al. Robust Smooth Feature Extraction from Point Clouds[C]//Proceedings of the IEEE International Conference on Shape Modeling and Applications. Lyon: IEEE,2007: 123-136.
[5] MEHDI-SOUZANI C, DIGNE J, AUDFRAY N, et al. Feature Extraction from High-density Point Clouds: Toward Automation of an Intelligent 3D Contactless Digitizing Strategy[J]. Computer-aided Design and Applications, 2010, 7(6): 863-874.
[6] WEBER C, HAHMANN S, HAGEN H. Methods for Feature Detection in Point Clouds[C]//Visualization of Large and Unstructured Data Sets: Applications in Geospatial Planning, Modeling and Engineering. Bodega Bay, CA: Schloss Dagstuhl-Leibniz-Zentrum fuer Informatik, 2011: 90-99.
[7] SURMANN H, LINGEMANN K, NVCHTER A, et al. A 3D Laser Range Finder for Autonomous Mobile Robots[C]//Proceedings of the 32nd International Symposium on Robotics. [S. l.]: ISR, 2001: 153-158.
[8] PAN Guorong, GU Chuan, WANG Suihui, et al. Research on Fitting Line Automatic Extraction Algorithm of 3D Laser Scanning[J]. Journal of Geodesy and Geodynamics, 2009, 29(1): 57-63. (潘国荣, 谷川, 王穗辉, 等. 三维激光扫描拟合直线自动提取算法研究[J]. 大地测量与地球动力学, 2009, 29(1): 57-63.)
[9] FERNÁNDEZ C, MORENO V, CURTO B, et al. Clustering and Line Detection in Laser Range Measurements[J]. Robotics and Autonomous Systems, 2010, 58(5): 720-726.
[10] MOVAFAGHPOUR M A, MASEHIAN E. Poly Line Map Extraction in Sensor-based Mobile Robot Navigation Using a Consecutive Clustering Algorithm[J]. Robotics and Autonomous Systems, 2012, 60(8): 1078-1092.
[11] NOROUZI M, YAGHOBI M, SIBONI M R, et al. Recursive Line Extraction Algorithm from 2D Laser Scanner Applied to Navigation a Mobile Robot[C]//Proceedings of the IEEE International Conference on Robotics and Biomimetics. Bangkok: IEEE, 2009: 2127-2132.
[12] SUI L C. Processing of Laser Scanner Data and Extraction of Structure Lines Using Methods of the Image Processing[J]. Acta Geodaetica et Cartographica Sinica, 2004, 33(1): 63-70.
[13] JIANG X, BUNKE H. Edge Detection in Range Images Based on Scan Line Approximation[J]. Computer Vision and Image Understanding, 1999, 73(2): 183-199.
[14] DENG Fei. Research on LiDAR and Digital Images Registration and Objects Extraction[D]. Wuhan: Wuhan University, 2006. (邓非. LiDAR数据与数字影像的配准和地物提取研究 [D]. 武汉: 武汉大学, 2006.)
[15] ZHAN Qingming, ZHOU Xingang, XIAO Yinghui, et al. Comparison of Linear and Circular Feature Extraction Methods Based on Laser Point Clouds of an Ancient Architecture[J]. Geomatics and Information Science of Wuhan University, 2011, 36(6): 674-677.(詹庆明, 周新刚, 肖映辉, 等. 从激光点云中提取古建筑线性和圆形特征的比较[J]. 武汉大学学报: 信息科学版, 2011, 36(6): 674-677.)
[16] LU Z J, BAEK S, LEE S. Robust 3D Line Extraction from Stereo Point Clouds[C]//Proceedings of the IEEE Conference on Robotics, Automation and Mechatronics. Chengdu: IEEE, 2008: 1-5.
[17] MEIERHOLD N, SCHMICH A. Referencing of Images to Laser Scanner Data Using Linear Features Extracted from Digital Images and Range Images[C]//Proceedings of the ISPRS Workshop Laser Scanning 2009. [S. l.]: ISPRS, 2010: 210-219.
[18] LEE S, KIM E, PARK Y. 3D Object Recognition Using Multiple Features for Robotic Manipulation[C]//Proceedings of the 2006 IEEE International Conference on Robotics and Automation. Orlando, Florida: IEEE , 2006: 3768-3774.
[19] ZHANG Fan, HUANG Xianfeng, LI Deren. Spherical Projection Based Triangulation for One Station Terrestrial Laser Scanning Point Cloud[J]. Acta Geodaetica et Cartographica Sinica, 2009, 38(1): 48-54. (张帆, 黄先锋, 李德仁. 基于球面投影的单站地面激光扫描点云构网方法 [J]. 测绘学报, 2009, 38(1): 48-54.)
[20] SHAH T R. Automatic Reconstruction of Industrial Installations Using Point Clouds and Images[D]. Delft: Technische Universiteit Delft, 2006.
[21] ARFKEN G B. Mathematical Methods for Physicists[M]. 6th ed. Orlando, FL: Academic Press, 2005.
[22] BRIESE C. Structure Line Modelling Based on Terrestrial Laser Scanner Data[C]//Proceedings of the ISPRS Symposium on Image Engineering and Vision Metrology. Dresden: ISPRS, 2006: 129-136.
[23] MEER P, GEORGESCU B. Edge Detection with Embedded Confidence[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2001, 23(12): 1351-1365.
[24] CANNY J. A Computational Approach to Edge Detection[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 1986, 8(6): 679-698.
[25] ZHANG F, HUANG X F, CHENG X G, et al. Edge Extraction Algorithm Based on Linear Perception Enhancement[C]//Proceedings of the International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences. Beijing: ISPRS, 2008: 497-502.
[26] FISCHLER M A, BOLLES R C. Random Sample Consensus: A Paradigm for Model Fitting with Applications to Image Analysis and Automated Cartography[J]. Communications of the ACM, 1981, 24(6): 381-395.
Options
Outlines

/

〈 〉