Robust detection and matching algorithm oriented to near infrared cooperative objects

Shuai Hao, Yong Mei Cheng, Xu Ma, Lin Song, Jian Tao Zhao

Research output: Contribution to journalArticlepeer-review

3 Scopus citations

Abstract

In order to overcome the problem of cooperative object detection susceptible to disturbance in vision relative navigation for unmanned aerial vehicle (UAV) carrier landing, a robust detection and matching algorithm based on near infrared cooperative objects is proposed. Firstly, an imaging system based on near infrared cooperative objects with 850 nm is constructed. For the cooperative object image, a method of spatial geometric constraints is designed to remove the alien interference points. And Hu invariant moments are used to further filter out the similar interference points. Finally, a matching method based on shape context is adopted to deal with the difficulty in cooperative object matching due to the distortion of scale and angle. Experimental results show that the proposed algorithm can achieve cooperative object detection and matching robustly with different distances, different lights, different angles and environment disturbance.

Original languageEnglish
Pages (from-to)1854-1859
Number of pages6
JournalXi Tong Gong Cheng Yu Dian Zi Ji Shu/Systems Engineering and Electronics
Volume36
Issue number9
DOIs
StatePublished - 1 Sep 2014

Keywords

  • Hu invariant moments
  • Near infrared cooperative object
  • Shape context
  • Spatial geometric constraints
  • Vision landing

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