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Journal of the Indian Society of Remote Sensing

, Volume 46, Issue 12, pp 2057–2068 | Cite as

Automatic Building Extraction from Image and LiDAR Data with Active Contour Segmentation

  • Zeynep Akbulut
  • Samed Özdemir
  • Hayrettin Acar
  • Fevzi Karsli
Research Article
  • 52 Downloads

Abstract

Automatic building extraction is an important topic for many applications such as urban planning, disaster management, 3D building modeling and updating GIS databases. Its approaches mainly depend on two data sources: light detection and ranging (LiDAR) point cloud and aerial imagery both of which have advantages and disadvantages of their own. In this study, in order to benefit from the advantages of each data sources, LiDAR and image data combined together. And then, the building boundaries were extracted with the automated active contour algorithm implemented in MATLAB. Active contour algorithm uses initial contour positions to segment an object in the image. Initial contour positions were detected without user interaction by a series of image enhancements, band ratio and morphological operations. Four test areas with varying building and background levels of detail were selected from ISPRS’s benchmark Vaihingen and Istanbul datasets. Vegetation and shadows were removed from all the datasets by band ratio to improve segmentation quality. Subsequently, LiDAR point cloud data was converted to raster format and added to the aerial imagery as an extra band. Resulting merged image and initial contour positions were given to the active contour algorithm to extract building boundaries. In order to compare the contribution of LiDAR to the proposed method, the boundaries of the buildings were extracted from the input image before and after adding LiDAR data to the image as a layer. Finally extracted building boundaries were smoothed by the Awrangjeb (Int J Remote Sen 37(3): 551–579.  https://doi.org/10.1080/01431161.2015.1131868, 2016) boundary regularization algorithm. Correctness (Corr), completeness (Comp) and accuracy (Q) metrics were used to assess accuracy of segmented building boundaries by comparing extracted building boundaries with manually digitized building boundaries. Proposed approach shows the promising results with over 93% correctness, 92% completeness and 89% quality.

Keywords

Active contour Automatic Building extraction High-resolution image LiDAR 

Notes

Acknowledgements

The authors express their gratitude to German Society for Photogrammetry, Remote Sensing and Geoinformation (DGPF) for ISPRS Vaihingen dataset. Also authors acknowledge The Istanbul Metropolitan Municipality for Istanbul datasets.

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Copyright information

© Indian Society of Remote Sensing 2018

Authors and Affiliations

  1. 1.Department of Geomatics, Faculty of EngineeringGumushane UniversityGumushaneTurkey
  2. 2.Department of Geomatics, Faculty of EngineeringKaradeniz Technical UniversityTrabzonTurkey

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