• Journal of the Korean Society of Tobacco Science
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• v.28 no.2
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• pp.144-151
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• 2006

A measurement uncertainty for analysis of volatile organic compound (benzene) in cigarette mainstream smoke was carried out. In this study one point re-calibration method was used to estimate uncertainty for benzene. The measurement uncertainty was calculated based on the uncertainty sources of each analysis step, quality appraisal sources, drift and repeatability. As a result, the concentration and expanded uncertainty of benzene in cigarette mainstream smoke were measured as $38.08{\pm}4.36{\mu}g/cig$. Relative uncertainty of drift and repeatability obtained were 5% and 3%, respectively.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.4
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• pp.621-628
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• 2021

This paper proposes a method to calibrate a thermal camera with three different perspectives. In particular, the intrinsic parameters of the camera and re-projection errors were provided to quantify the accuracy of the calibration result. Three lenses of the camera capture the same image, but they are not overlapped, and the image resolution is worse than the one captured by the RGB camera. In computer vision, camera calibration is one of the most important and fundamental tasks to calculate the distance between camera (s) and a target object or the three-dimensional (3D) coordinates of a point in a 3D object. Once calibration is complete, the intrinsic and the extrinsic parameters of the camera(s) are provided. The intrinsic parameters are composed of the focal length, skewness factor, and principal points, and the extrinsic parameters are composed of the relative rotation and translation of the camera(s). This study estimated the intrinsic parameters of thermal cameras that have three lenses of different perspectives. In particular, image enhancement based on a deep learning algorithm was carried out to improve the quality of the calibration results. Experimental results are provided to substantiate the proposed method.