Underwater image matching by incorporating structural constraints
Yang, Xu1; Liu, Zhi-Yong1,2,3; Qiao, Hong1,2,3; Song, Yong-Bo1; Ren, Shu-Nan1; Ji, Da-Xiong4; Zheng, Sui-Wu1,5
Source PublicationINTERNATIONAL JOURNAL OF ADVANCED ROBOTIC SYSTEMS
2017-12-20
Volume14Issue:6Pages:0
SubtypeArticle
AbstractUnderwater robot plays an important role in underwater perception and manipulation tasks. Vision information processing is essential for the intelligent perception of an underwater robot, in which image matching is a fundamental topic. Feature-based image matching is suitable for the underwater environment. However, current underwater image matching usually directly applies those methods with a general purpose or designed for images obtained from the land to underwater images. The problem is that the blurring appearance caused feature descriptor ambiguity, which may greatly deteriorate the performance of these methods on underwater images. Aiming at problem, this article provides an underwater image matching framework by incorporating structural constraints. By integrating the appearance descriptor and structural information by a graph model, the feature correspondence-based image matching is formulated and solved by a graph matching method. Particularly, to solve the outlier feature problem, the graph matching method is applicable to the case where outlier features exist in both underwater images. Experiments on both synthetic points and real-world underwater images validate the effectiveness of the proposed method.
Other Abstract
KeywordUnderwater Image Image Matching Underwater Robot Feature Correspondence
WOS HeadingsScience & Technology ; Technology
DOI10.1177/1729881417738100
WOS KeywordGRAPH ; GNCCP
Indexed BySCI
Language英语
Funding OrganizationNational Natural Science Foundation of China(61503383 ; National Key Research and Development Plan of China(2016YFC0300801) ; Beijing Municipal Science and Technology(D16110400140000 ; Guangdong Science and Technology Department(2016B090910001) ; 61633009 ; D161100001416001) ; U1613213 ; 61375005 ; 61210009 ; 61773047)
WOS Research AreaRobotics
WOS SubjectRobotics
WOS IDWOS:000418542000001
Citation statistics
Document Type期刊论文
Identifierhttp://ir.ia.ac.cn/handle/173211/15487
Collection复杂系统管理与控制国家重点实验室_机器人理论与应用
Affiliation1.Chinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Zhongguancun East Rd 95, Beijing 100190, Peoples R China
2.Chinese Acad Sci, Ctr Excellence Brain Sci & Intelligence Technol, Shanghai, Peoples R China
3.Univ Chinese Acad Sci, Beijing, Peoples R China
4.Zhejiang Univ, Ocean Coll, Zhoushan, Peoples R China
5.Huizhou Adv Mfg Technol Res Ctr Co Ltd, Huizhou 516000, Peoples R China
First Author AffilicationInstitute of Automation, Chinese Academy of Sciences
Recommended Citation
GB/T 7714
Yang, Xu,Liu, Zhi-Yong,Qiao, Hong,et al. Underwater image matching by incorporating structural constraints[J]. INTERNATIONAL JOURNAL OF ADVANCED ROBOTIC SYSTEMS,2017,14(6):0.
APA Yang, Xu.,Liu, Zhi-Yong.,Qiao, Hong.,Song, Yong-Bo.,Ren, Shu-Nan.,...&Zheng, Sui-Wu.(2017).Underwater image matching by incorporating structural constraints.INTERNATIONAL JOURNAL OF ADVANCED ROBOTIC SYSTEMS,14(6),0.
MLA Yang, Xu,et al."Underwater image matching by incorporating structural constraints".INTERNATIONAL JOURNAL OF ADVANCED ROBOTIC SYSTEMS 14.6(2017):0.
Files in This Item: Download All
File Name/Size DocType Version Access License
Underwater Image Mat(57KB)期刊论文作者接受稿开放获取CC BY-NC-SAView Download
Related Services
Recommend this item
Bookmark
Usage statistics
Export to Endnote
Google Scholar
Similar articles in Google Scholar
[Yang, Xu]'s Articles
[Liu, Zhi-Yong]'s Articles
[Qiao, Hong]'s Articles
Baidu academic
Similar articles in Baidu academic
[Yang, Xu]'s Articles
[Liu, Zhi-Yong]'s Articles
[Qiao, Hong]'s Articles
Bing Scholar
Similar articles in Bing Scholar
[Yang, Xu]'s Articles
[Liu, Zhi-Yong]'s Articles
[Qiao, Hong]'s Articles
Terms of Use
No data!
Social Bookmark/Share
File name: Underwater Image Matching by Incorporating Structural Constraints_Acceptance.pdf
Format: Adobe PDF
All comments (0)
No comment.
 

Items in the repository are protected by copyright, with all rights reserved, unless otherwise indicated.