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Corner detection and matching for infrared image based on double ring mask and adaptive SUSAN algorithm

  • Xu Chen
  • Lei Liu
  • Jiaxiao Song
  • Yefei Li
  • Zhuang Zhang
Article

Abstract

Infrared (IR) image fusion is designed to fuse several IR images into a comprehensive image to boost imaging quality and reduce redundancy information, and image matching is an indispensable step. However, Conventional matching techniques are susceptible to the noise and fuzzy edges in IR images and it is therefore very desirable to have a matching algorithm that is tolerant to them. This paper presents a method for infrared image matching based on the SUSAN corner detection. To solve the problems of the traditional SUSAN algorithm including the fixed threshold of gray value difference and the failed detection of symmetry corners, an adaptive threshold extraction method is raised in this study. Furthermore, an attached double ring mask is used to improve the complex corner detection capability. A constraint condition and a principle of gravity are adopted to filtrate the candidate corners. The proposed method is qualitatively and quantitatively evaluated on IR images in the experiments. In comparison with other methods, better performance has been achieved.

Keywords

Infrared image matching SUSAN Adaptive threshold Double ring mask 

Notes

Acknowledgements

This work is sponsored by Qing Lan Project of Jiangsu Province-China, the Fundamental Research Funds for the Central Universities-China (Grant No. 30916011206) and the Six Talent Peaks Project in Jiangsu Province-China (Grant No. 2015-XCL-008).

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Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  • Xu Chen
    • 1
  • Lei Liu
    • 1
  • Jiaxiao Song
    • 1
  • Yefei Li
    • 1
  • Zhuang Zhang
    • 1
  1. 1.School of Electronic and Optical EngineeringNanjing University of Science and TechnologyNanjingChina

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