A robust line matching method based on local appearance descriptor and neighboring geometric attributes

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

Abstract

This paper reports an efficient method for line matching, which utilizes local intensity gradient information and neighboring geometric attributes. Lines are detected in a multi-scale way to make the method robust to scale changes. A descriptor based on local appearance is built to generate candidate matching pairs. The key idea is to accumulate intensity gradient information into histograms based on their intensity orders to overcome the fragmentation problem of lines. Besides, local coordinate system is built for each line to achieve rotation invariance. For each line segment in candidate matching pairs, a histogram is built by aggregating geometric attributes of neighboring line segments. The final matching measure derives from the distance between normalized geometric attributes histograms. Experiments show that the proposed method is robust to large illumination changes and is rotation invariant.

Original languageEnglish
Title of host publicationInfrared Technology and Applications, and Robot Sensing and Advanced Control
EditorsHaimei Gong, Aiguo Song
PublisherSPIE
ISBN (Electronic)9781510607729
DOIs
StatePublished - 2016
EventInternational Symposium on Infrared Technology and Application and the International Symposiums on Robot Sensing and Advanced Control - Beijing, China
Duration: 9 May 201611 May 2016

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering
Volume10157
ISSN (Print)0277-786X
ISSN (Electronic)1996-756X

Conference

ConferenceInternational Symposium on Infrared Technology and Application and the International Symposiums on Robot Sensing and Advanced Control
Country/TerritoryChina
CityBeijing
Period9/05/1611/05/16

Keywords

  • Line matching
  • intensity order
  • local coordinate system
  • multi-scale line extraction
  • neighboring geometric attributes

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