AN INTEGRATED SYSTEM ON LARGE SCALE BUILDING EXTRACTION FROM DSM

被引:3
|
作者
Li, Y. [1 ]
Zhu, L. [2 ]
Shimamura, H. [2 ]
Tachibana, K. [2 ]
机构
[1] Nanjing Univ, Int Inst Earth Syst Sci, Nanjing 210093, Jiangsu, Peoples R China
[2] Pasco Corp, Meguro Ku, Tokyo 1530043, Japan
关键词
Building extraction; DSM; Morphology; Level set; Watershed; SEGMENTATION;
D O I
10.1145/1854776.1854787
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Large scale automatic building extraction is difficult in Japan, because of the high density of buildings and various roof types especially in the residential area. We propose an automatic and integrated system for building extraction from DSM, in order to model the outlines of the buildings in 2D plane. In our previous research, the building extraction based on foreground/background marker gives good result and most buildings can be detected. However, it is still difficult to model the building because the shape is not accurate enough. The active contour is a kind of segmentation method widely used in medical image processing. It merges edge detection into gray segmentation so that the contour converges at the right edge of the certain object. It can be employed locally on the DSM to obtain the outline of a building if the initial contour is given to close to the building. Thus we developed a scheme of accurately locating the building by marker controlled watershed and accurately segmenting the building by active contour. There are two basic processes in this scheme. First is the initial building segmentation, or the building location. Watershed of the gradient of the DSM can get the objects' contour. To avoid over segmentation, the markers of the terrain and the off-terrain must be labelled and set to local minimal. There are three types of markers to be labelled, including two of buildings and one of terrain. The methods of marker labelling for small houses and big houses are different. The markers of the small houses are decided by local maximum of DSM, while those of the big or high buildings are extracted using area morphology method. The terrain markers are detected by the watershed of the DSM not crossing the building markers. The marker controlled watershed segmentation on the gradient of the DSM gives the contours of the off-terrain objects. Then, each building object is used as a mask by enlarging its size, and active contour method is implemented to segment the masked DSM to obtain the subtle contour of the building. Level set as a typical solution of active contour is employed because of its fast iterating process. The contour of the level set can be converged exactly at the outline of the building for a local DSM including only one house. RGB image can be used instead of DSM, but the result is not as good as that of DSM. These methods and scheme construct a system of large scale and automatic building extraction. The experiment in Saitama, Japan is given as the evaluation of the proposed system.
引用
收藏
页码:35 / 39
页数:5
相关论文
共 50 条
  • [31] Large-scale LOD1 Building Extraction from a Textured 3D Mesh of a Scene
    Duan, Liuyun
    Swaine, Michael
    Tripodi, Sebastien
    Cherif, Mohamed A.
    Gobbin, Arno
    Girard, Nicolas
    Tarabalka, Yuliya
    Laurore, Lionel
    IMAGE AND SIGNAL PROCESSING FOR REMOTE SENSING XXIX, 2023, 12733
  • [32] Predicting building age from urban form at large scale
    Nachtigall, Florian
    Milojevic-Dupont, Nikola
    Wagner, Felix
    Creutzig, Felix
    COMPUTERS ENVIRONMENT AND URBAN SYSTEMS, 2023, 105
  • [33] Dynamic Model and Intelligent Maximum Power Point Tracking Approach for Large-Scale Building-Integrated Photovoltaic System
    An, Qing
    Tang, Ruoli
    Su, Hongfeng
    ENERGY TECHNOLOGY, 2021, 10 (02)
  • [34] Fast FDTD Method for Large-Scale Layout Extraction and Analysis of Integrated Circuits
    Xue, Li
    Jiao, Dan
    2018 IEEE ANTENNAS AND PROPAGATION SOCIETY INTERNATIONAL SYMPOSIUM ON ANTENNAS AND PROPAGATION & USNC/URSI NATIONAL RADIO SCIENCE MEETING, 2018, : 1157 - 1158
  • [35] Large-Scale Entity Extraction from Enterprise Data
    Gupta, Rajeev
    Kondapally, Ranganath
    SECOND INTERNATIONAL CONFERENCE ON AIML SYSTEMS 2022, 2022,
  • [36] Large-Scale Extraction and Use of Knowledge from Text
    Clark, Peter
    Harrison, Phil
    K-CAP'09: PROCEEDINGS OF THE FIFTH INTERNATIONAL CONFERENCE ON KNOWLEDGE CAPTURE, 2009, : 153 - 160
  • [37] INTEGRATED EDP-SYSTEM FOR MEDIUM-SCALE MACHINE-BUILDING
    HAMMER, K
    F&M-FEINWERKTECHNIK & MESSTECHNIK, 1988, 96 (10): : CA92 - &
  • [38] On the provenance extraction techniques from large scale log files
    Tufek, Alper
    Aktas, Mehmet S.
    CONCURRENCY AND COMPUTATION-PRACTICE & EXPERIENCE, 2023, 35 (15):
  • [39] Hazardous wastes from large-scale metal extraction
    Anon
    Environmental Science and Technology, 1990, 24 (09):
  • [40] A Diverse Large-Scale Building Dataset and a Novel Plug-and-Play Domain Generalization Method for Building Extraction
    Luo, Muying
    Ji, Shunping
    Wei, Shiqing
    IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING, 2023, 16 : 4122 - 4138