Determining relative position and attitude of a close non-cooperative target based on the SIFT algorithm

Wei Wei Hao, Xiao Fang Zhang*, Yu Huang, Feng Yang, Bai Wei Guo

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)

Abstract

A binocular stereo vision positioning method based on the scale-invariant feature transform (SIFT) algorithm is proposed. The SIFT algorithm is for extracting distinctive invariant features from images. First, image median filtering is used to eliminate image noise. Then, according to the characteristics of the target satellite, image map is used to extract the middle part of the target satellite. At last, the feature match point under the SIFT algorithm is extracted, and the three-dimensional position and orientation are calculated. The features are invariant to image scale and rotation, and are shown to provide robust matching across a substantial range of affine distortion, change in 3D viewpoint, addition of noise, and change in illumination. The experimental result shows that the algorithm works well and the maximum relative error is within 0.02 m and 2.5°.

Original languageEnglish
Pages (from-to)390-394
Number of pages5
JournalJournal of Beijing Institute of Technology (English Edition)
Volume23
Issue number3
Publication statusPublished - 1 Sept 2014

Keywords

  • Binocular stereo vision
  • Image matching
  • Pose measurement
  • SIFT algorithm

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