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http://dx.doi.org/10.7848/ksgpc.2019.37.6.545

A Hybrid Approach for Automated Building Area Extraction from High-Resolution Satellite Imagery  

An, Hyowon (Dept. of Civil and Environmental Engineering, Myongji University)
Kim, Changjae (Dept. of Civil and Environmental Engineering, Myongji University)
Lee, Hyosung (Dept. of Civil Engineering, Sunchon National University)
Kwon, Wonsuk (Agency for Defense Development)
Publication Information
Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography / v.37, no.6, 2019 , pp. 545-554 More about this Journal
Abstract
This research aims to provide a building area extraction approach over the areas where data acquisition is impossible through field surveying, aerial photography and lidar scanning. Hence, high-resolution satellite images, which have high accessibility over the earth, are utilized for the automated building extraction in this study. 3D point clouds or DSM (Digital Surface Models), derived from the stereo image matching process, provides low quality of building area extraction due to their high level of noises and holes. In this regards, this research proposes a hybrid building area extraction approach which utilizes 3D point clouds (from image matching), and color and linear information (from imagery). First of all, ground and non-ground points are separated from 3D point clouds; then, the initial building hypothesis is extracted from the non-ground points. Secondly, color based building hypothesis is produced by considering the overlapping between the initial building hypothesis and the color segmentation result. Afterwards, line detection and space partitioning results are utilized to acquire the final building areas. The proposed approach shows 98.44% of correctness, 95.05% of completeness, and 1.05m of positional accuracy. Moreover, we see the possibility that the irregular shapes of building areas can be extracted through the proposed approach.
Keywords
High-Resolution Satellite Imagery; Stereo Image Matching; Building Hypothesis Generation; Color based Image Segmentation; Line Detection and Space Partitioning; Building Area Extraction;
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Times Cited By KSCI : 1  (Citation Analysis)
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