A Robust Insulator Detection Algorithm Based on Local Features and Spatial Orders for Aerial Images

被引:89
作者
Liao, Shenglong [1 ]
An, Jubai [1 ]
机构
[1] Dalian Maritime Univ, Informat Sci & Technol Coll, Dalian 116026, Peoples R China
基金
美国国家科学基金会;
关键词
Aerial image; insulator detection; local feature; point matching; spatial orders; REPRESENTATION;
D O I
10.1109/LGRS.2014.2369525
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
The detection of targets with complex backgrounds in aerial images is a challenging task. In this letter, we propose a robust insulator detection algorithm based on local features and spatial orders for aerial images. First, we detect local features and introduce a multiscale and multifeature descriptor to represent the local features. Then, we get several spatial orders features by training these local features, it improves the robustness of the algorithm. Finally, through a coarse-to-fine matching strategy, we eliminate background noise and determine the region of insulators. We test our method on a diverse aerial image set. The experimental results demonstrate the precision and robustness of our detection method, and indicate the possible use of our method in practical applications.
引用
收藏
页码:963 / 967
页数:5
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