KEYWORDS: Point clouds, Cameras, Calibration, Singular value decomposition, Imaging systems, 3D metrology, Matrices, Fringe analysis, Deformation, 3D projection
Fringe projection profilometry 3D measurement technology has been widely used in industrial inspection due to its high measurement accuracy, fast speed, and non-contact characteristics. Under normal working conditions, fringe projection profilometry measurement technology can achieve high working performance. However, the characteristics of train wheelsets, such as large size, large bending potential, and high measurement accuracy requirements, make it difficult to apply traditional fringe projection profilometry 3D measurement technology in the measurement of train wheelsets. In the actual measurement, it is necessary to measure the inner base surface and the outer base surface of the train wheelset at the same time, resulting in a large stereo calibration error caused by the non-parallel optical center of the cameras. A calibration method based on singular value segmentation (SVD) is proposed. The experimental results show the effectiveness of the proposed calibration method and improve the measurement accuracy of the wheel tread.
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