A correction method for radial distortion and nonlinear response of infrared cameras

• Published in: Review of scientific instruments 2024-03, Vol.95 (3)
• Main Authors: Shu, Shuangbao, Fu, Yufeng, Liu, Shenglin, Zhang, Yuzhong, Zhang, Tengda, Wu, Tianqi, Gao, Xinyu
• Format: Article
• Language: English
• Subjects: Accuracy; Body temperature; Calibration; Cameras; Distortion; Error analysis; Error correction; Infrared cameras; Infrared imaging; Nonlinear response; Parameters; Temperature measurement
• ISSN: 0034-6748; 1089-7623
• DOI: 10.1063/5.0187807

The key feature of non-contact temperature measurement provided by infrared (IR) cameras underpins their versatility. However, the accuracy of temperature measurements with IR cameras depends on imaging quality due to their non-contact nature, such as the lens, body temperature, and measurement environment. This paper addresses the correction of radial distortion and nonlinear response issues in IR cameras. To address radial distortion, we have designed a passive checkerboard calibration board specifically for infrared cameras. This board is used to calibrate the IR camera and derive the necessary camera parameters. Subsequently, these parameters are applied during the actual measurement process to rectify radial distortion effectively. Building on the radial distortion correction method mentioned above, we propose a multi-point segmented calibration approach that considers different temperature ranges and imaging regions. This method alleviates the issue of reduced temperature measurement accuracy due to variations in camera responses by computing gain and offset coefficient matrices for each temperature range. Experimental results demonstrate the effectiveness of the calibration board in correcting radial distortion in IR cameras, with a mean reprojection error of less than 0.16 pixels. Regarding the nonlinear response problem, the introduced method significantly reduces the relative error in temperature measurement. In the verification phase, spanning from 100 to 500 °C, the average relative error in temperature measurement decreases by 0.49% from 1.61% before and after correction, which highlights a substantial improvement in temperature measurement accuracy. This work gives a useful reference to improve the imaging quality and temperature measurement accuracy using infrared cameras.