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基于分层搜索与局部约束线性编码的机场检测

Airport Detection Based on a Hierarchical Architecture and Locality-Constrained Linear Coding

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摘要

提出一种用于固定翼无人机自主着陆导航的分层机场检测方法,以提高机场检测的速度。采取一种由粗到细的分层搜索结构,逐层缩小搜索面积以快速提取机场的候选区域。首先进行伪地平线检测将机场搜索区域限制为地面区域,然后根据机场区域包含大量垂直线的事实确定机场近似区域候选区以进一步缩小机场搜索区域,最后利用Edge Boxes得到高定位精度的机场候选区域。利用局部约束线性编码(LLC)特征学习法以尺度不变特征变换(SIFT)为基础特征提取机场候选区域特征并使用线性支持向量机(SVM)分类器完成机场检测。实验中在不同天气、不同背景条件下对所提机场检测方法进行了综合测试,并与其他方法进行比较,实验结果表明本文机场检测方法能有效提高机场检测速度,且准确率高。

Abstract

An airport detection method is proposed for the navigation of fixed-wing unmanned aerial vehicle (UAV) autonomous landing in this paper, which aims at improving the efficiency of detection. A hierarchical architecture is adopted to obtain airport candidate regions which reduces the search space gradually. The pseudo horizon is detected to limit the searching space to the ground area, then candidate approximate airport area is acquired based on the fact that the airport area contains lots of orthogonal line segments. Edge Boxes is adopted to obtain proposals with good localization on the candidate approximate airport areas. Locality-constrained linear coding (LLC) is used for feature extraction with scale-invariant feature transformation (SIFT) as the basic features and linear support vector machine (SVM) is used to finish the task of airport detection. We evaluate the proposed method under different conditions and compare it with other methods. The results show that our method improves the efficiency of airport detection and has a higher average precision.

Newport宣传-MKS新实验室计划
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中图分类号:V249

DOI:10.3788/aos201838.0815025

所属栏目:“机器视觉检测与应用”专题

收稿日期:2018-04-02

修改稿日期:2018-05-02

网络出版日期:2018-05-30

作者单位    点击查看

胡运强:南京航空航天大学自动化学院, 江苏 南京 210016
曹云峰:南京航空航天大学航天学院, 江苏 南京 210016
丁萌:南京航空航天大学民航学院, 江苏 南京 210016
庄丽葵:南京航空航天大学航天学院, 江苏 南京 210016

联系人作者:胡运强(hupenghyq@163.com)

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引用该论文

Hu Yunqiang,Cao Yunfeng,Ding Meng,Zhuang Likui. Airport Detection Based on a Hierarchical Architecture and Locality-Constrained Linear Coding[J]. Acta Optica Sinica, 2018, 38(8): 0815025

胡运强,曹云峰,丁萌,庄丽葵. 基于分层搜索与局部约束线性编码的机场检测[J]. 光学学报, 2018, 38(8): 0815025

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