Robust image matching via ORB feature and VFC for mismatch removal

Tao Ma, Wenxing Fu, Bin Fang, Fangyu Hu, Siwen Quan, Jie Ma

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Image matching is at the base of many image processing and computer vision problems, such as object recognition or structure from motion. Current methods rely on good feature descriptors and mismatch removal strategies for detection and matching. In this paper, we proposed a robust image match approach based on ORB feature and VFC for mismatch removal. ORB (Oriented FAST and Rotated BRIEF) is an outstanding feature, it has the same performance as SIFT with lower cost. VFC (Vector Field Consensus) is a state-of-the-art mismatch removing method. The experiment results demonstrate that our method is efficient and robust.

Original languageEnglish
Title of host publicationMIPPR 2017
Subtitle of host publicationPattern Recognition and Computer Vision
EditorsChao Cai, Zhiguo Cao, Yuehuang Wang
PublisherSPIE
ISBN (Electronic)9781510617216
DOIs
StatePublished - 2017
Externally publishedYes
Event10th International Symposium on Multispectral Image Processing and Pattern Recognition, MIPPR 2017 - Xiangyang, China
Duration: 28 Oct 201729 Oct 2017

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering
Volume10609
ISSN (Print)0277-786X
ISSN (Electronic)1996-756X

Conference

Conference10th International Symposium on Multispectral Image Processing and Pattern Recognition, MIPPR 2017
Country/TerritoryChina
CityXiangyang
Period28/10/1729/10/17

Keywords

  • Image matching
  • local invariant feature
  • ORB feature
  • vector field consensus

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