MURAL - Maynooth University Research Archive Library

    Linear Feature Extraction of Buildings from Terrestrial LIDAR Data with Morphological Techniques

    Zheng, Jianghua and McCarthy, Tim and Fotheringham, Stewart and Yan, Lei (2008) Linear Feature Extraction of Buildings from Terrestrial LIDAR Data with Morphological Techniques. In: The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences. International Society for Photogrammetry and Remote Sensing (ISPRS), pp. 241-244.

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    LiDAR has been a major interest of photogrammetry to acquire three dimensional objects. It has shown its promising capabilities in building virtual reality applications, such as virtual campus and virtual historic sites. However, point clouds of LiDAR data always occupy a large sum of storage capacity. This blocks further fast processing of LiDAR data to combine with GIS to build virtual reality. The research focused on linear feature extraction of buildings from terrestrial LiDAR data. To obtain linear features of buildings is one of the critical steps to realize minimization of redundant data and high efficiency of data processing. The paper discussed the procedure of linear features extracting of buildings and mainly put forward edge detection algorithms based on fractal dimension theory. Triangular method was chosen to obtain fractal dimension values of grids. The algorithm was not only effective and efficient to detect building edges, but also helpful for segmenting the building and nature objects. Future work was also discussed in the end.

    Item Type: Book Section
    Additional Information: Published under the Creative Common Attribution 3.0 License, see for details.
    Keywords: LIDAR; Terrestrial; Feature; Extraction; Edge; Detection; Building;
    Academic Unit: Faculty of Science and Engineering > Research Institutes > National Centre for Geocomputation, NCG
    Item ID: 9259
    Depositing User: Tim McCarthy
    Date Deposited: 19 Feb 2018 15:45
    Publisher: International Society for Photogrammetry and Remote Sensing (ISPRS)
    Refereed: Yes
    Use Licence: This item is available under a Creative Commons Attribution Non Commercial Share Alike Licence (CC BY-NC-SA). Details of this licence are available here

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