Long-wave infrared (LWIR) cameras are essential for vision navigation tasks such as positioning and nighttime target identification. Their superior imaging capabilities excel in challenging weather conditions like fog, clouds, and rain. This paper introduces a low-cost circular calibration plate that addresses the insensitivity of LWIR cameras to traditional chessboard patterns. By leveraging variations in thermal reflectivity among different opaque materials, this solution eliminates the need for special heating and simplifies the calibration process, thereby reducing complexity and costs. Additionally, the calibration accuracy is enhanced through elliptical contour extraction from the pattern. The experimental results confirm that the method offers easy operation, reliable accuracy, and significant time and labor savings, showcasing its versatility in vision navigation fields such as scene matching positioning.

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Experimental Verification of a Fast and Low-Cost Calibration Approach for Long-Wave Infrared Cameras in Vision Navigation

  • Haoming Wang,
  • Jiahang Dong,
  • Yazhou Yue,
  • Xiaodong Zhang,
  • Qi Zhou,
  • Nan Liu,
  • Guanjie Wang,
  • JinJiang Wang,
  • Haofeng Jiang

摘要

Long-wave infrared (LWIR) cameras are essential for vision navigation tasks such as positioning and nighttime target identification. Their superior imaging capabilities excel in challenging weather conditions like fog, clouds, and rain. This paper introduces a low-cost circular calibration plate that addresses the insensitivity of LWIR cameras to traditional chessboard patterns. By leveraging variations in thermal reflectivity among different opaque materials, this solution eliminates the need for special heating and simplifies the calibration process, thereby reducing complexity and costs. Additionally, the calibration accuracy is enhanced through elliptical contour extraction from the pattern. The experimental results confirm that the method offers easy operation, reliable accuracy, and significant time and labor savings, showcasing its versatility in vision navigation fields such as scene matching positioning.