SVD-SURF based fast and robust scene matching algorithm

Yaojun Li, Quan Pan, Chunhui Zhao, Hui Liu, Jianghua Zhang

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

2 Scopus citations

Abstract

For position parameter estimation of aircraft, this dissertation presents a SVD-SURF-based wide-baseline robust scene matching algorithm. Firstly, we build SURF scale space based on the singular value features of real-time image and reference image. By using fast Hessian matrix maximum values, 64-dimensional SURF feature descriptors of aerial images wre calculated. Then, based on the trace of the Hessian matrix, we complete feature points matching. Finally, by using RANSAC algorithm, we removed the outliers for accurate position estimation. Experiments with two real aerial image sequences show that this algorithm is robust to image rotation, scale transformation and noise.

Original languageEnglish
Title of host publicationProceedings of the 32nd Chinese Control Conference, CCC 2013
PublisherIEEE Computer Society
Pages5005-5010
Number of pages6
ISBN (Print)9789881563835
StatePublished - 18 Oct 2013
Event32nd Chinese Control Conference, CCC 2013 - Xi'an, China
Duration: 26 Jul 201328 Jul 2013

Publication series

NameChinese Control Conference, CCC
ISSN (Print)1934-1768
ISSN (Electronic)2161-2927

Conference

Conference32nd Chinese Control Conference, CCC 2013
Country/TerritoryChina
CityXi'an
Period26/07/1328/07/13

Keywords

  • Hessian matrix
  • RANSAC
  • Scene matching
  • SURF
  • SVD

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