船舶与海洋工程

基于超像素空间关系特征的无人机影像拦河坝提取

  • 郭开贞 ,
  • 李颖 ,
  • 刘大刚
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  • (大连海事大学 航海学院,  辽宁 大连 116026)
郭开贞(1994 — ),男,硕士,E-mail:kaizhenguo@outlook.com.

收稿日期: 2020-02-24

  修回日期: 2020-03-25

  网络出版日期: 2020-03-25

基金资助

国家重点研发计划专项(2018YFB1600402).

Barrage extraction from UAV image based on superpixel spatial relationship feature

  • GUO Kai-zhen ,
  • LI Ying ,
  • LIU Da-gang
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  • (Navigation College, Dalian Maritime University, Dalian 116026, China)

Received date: 2020-02-24

  Revised date: 2020-03-25

  Online published: 2020-03-25

Supported by

 

摘要

针对目前无人机影像提取内河目标存在的人工解译依赖高等问题,提出一种基于超像素空间关系特征的内河设施提取算法.首先,采用简单线性迭代聚类(SLIC)算法分割无人机影像生成超像素;其次,对分割得到的超像素区域进行颜色及纹理特征计算,基于支持向量机(SVM)实现水陆分割;最后,基于空间关系特征实现拦河坝的自动提取.实验结果表明,该方法能够有效提取无人机影像中的拦河坝区域,对内河航运发展和航道设施监测具有一定的应用价值.

本文引用格式

郭开贞 , 李颖 , 刘大刚 . 基于超像素空间关系特征的无人机影像拦河坝提取[J]. 大连海事大学学报, 2020 , 46(2) : 89 -95 . DOI: 10.16411/j.cnki.issn1006-7736.2020.02.011

Abstract

In order to solve the problem of high dependence of the extraction of river targets from UAV images on human interpretation, an algorithm based on the feature of super-pixel spatial relationship was proposed. Firstly, the simple linear iterative clustering (SLIC) algorithm was used to segment the UAV image and generate the super-pixel. Secondly, the color and texture features of the super-pixel region obtained were calculated, and the land and water segmentation was realized based on support vector machine (SVM). Finally, the automatic extraction of barrage was realized based on the feature of spatial relation. The experimental results show that this method can effectively extract the barrage area in UAV image, which has certain application value for the development of inland navigation and the monitoring of waterway facilities.

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