Accurate Outline Extraction of Individual Building From Very High-Resolution Optical Images

被引:29
作者
Qin, Xuebin [1 ]
He, Shida [1 ]
Yang, Xiucheng [2 ]
Dehghan, Masood [1 ]
Qin, Qiming [3 ]
Jagersand, Martin [1 ]
机构
[1] Univ Alberta, Dept Comp Sci, Edmonton, AB T6G 2R3, Canada
[2] Univ Strasbourg, ICube Lab, F-67081 Strasbourg, France
[3] Peking Univ, Inst Remote Sensing & Geog Informat Syst, Sch Earth & Space Sci, Beijing 100871, Peoples R China
关键词
Building recognition; graph optimization; outline extraction; perceptual grouping; BOUNDARY; REGIONS;
D O I
10.1109/LGRS.2018.2857719
中图分类号
P3 [地球物理学]; P59 [地球化学];
学科分类号
0708 ; 070902 ;
摘要
This letter presents a novel approach for extracting accurate outlines of individual buildings from very high- resolution (0.1-0.4 m) optical images. Building outlines are defined as polygons here. Our approach operates on a set of straight line segments that are detected by a line detector. It groups a subset of detected line segments and connects them to form a closed polygon. Particularly, a new grouping cost is defined first. Second, a weighted undirected graph G(V,E) is constructed based on the endpoints of those extracted line segments. The building outline extraction is then formulated as a problem of searching for a graph cycle with the minimal grouping cost. To solve the graph cycle searching problem, the bidirectional shortest path method is utilized. Our method is validated on a newly created data set that contains 123 images of various building roofs with different shapes, sizes, and intensities. The experimental results with an average intersection-over-union of 90.56% and an average alignment error of 6.56 pixels demonstrate that our approach is robust to different shapes of building roofs and outperforms the state-of-the-art method.
引用
收藏
页码:1775 / 1779
页数:5
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