Mr. Chao Wang Profile

Chao Wang

at Xi’an Jiaotong Univ

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Proceedings Article | 6 September 2017 Paper

A novel 360-degree shape measurement using a simple setup with two mirrors and a laser MEMS scanner

Rui Jin, Xiang Zhou, Tao Yang, Dong Li, Chao Wang

Proceedings Volume 10410, 1041016 (2017) https://doi.org/10.1117/12.2276854

KEYWORDS: Calibration, Laser scanners, 3D scanning, Laser applications, Projection systems

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There is no denying that 360-degree shape measurement technology plays an important role in the field of threedimensional optical metrology. Traditional optical 360-degree shape measurement methods are mainly two kinds: the first kind, by placing multiple scanners to achieve 360-degree measurements; the second kind, through the high-precision rotating device to get 360-degree shape model. The former increases the number of scanners and costly, while the latter using rotating devices lead to time consuming. This paper presents a low cost and fast optical 360-degree shape measurement method, which possesses the advantages of full static, fast and low cost. The measuring system consists of two mirrors with a certain angle, a laser projection system, a stereoscopic calibration block, and two cameras. And most of all, laser MEMS scanner can achieve precise movement of laser stripes without any movement mechanism, improving the measurement accuracy and efficiency. What’s more, a novel stereo calibration technology presented in this paper can achieve point clouds data registration, and then get the 360-degree model of objects. A stereoscopic calibration block with special coded patterns on six sides is used in this novel stereo calibration method. Through this novel stereo calibration technology we can quickly get the 360-degree models of objects.

Proceedings Article | 6 September 2017 Paper

A three dimensional point cloud registration method based on rotation matrix eigenvalue

Chao Wang, Xiang Zhou, Zixuan Fei, Xiaofei Gao, Rui Jin

Proceedings Volume 10410, 1041014 (2017) https://doi.org/10.1117/12.2276849

KEYWORDS: Clouds, Imaging systems, Cameras, Calibration, 3D metrology, Optical testing, Image registration

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We usually need to measure an object at multiple angles in the traditional optical three-dimensional measurement method, due to the reasons for the block, and then use point cloud registration methods to obtain a complete threedimensional shape of the object. The point cloud registration based on a turntable is essential to calculate the coordinate transformation matrix between the camera coordinate system and the turntable coordinate system. We usually calculate the transformation matrix by fitting the rotation center and the rotation axis normal of the turntable in the traditional method, which is limited by measuring the field of view. The range of exact feature points used for fitting the rotation center and the rotation axis normal is approximately distributed within an arc less than 120 degrees, resulting in a low fit accuracy. In this paper, we proposes a better method, based on the invariant eigenvalue principle of rotation matrix in the turntable coordinate system and the coordinate transformation matrix of the corresponding coordinate points. First of all, we control the rotation angle of the calibration plate with the turntable to calibrate the coordinate transformation matrix of the corresponding coordinate points by using the least squares method. And then we use the feature decomposition to calculate the coordinate transformation matrix of the camera coordinate system and the turntable coordinate system. Compared with the traditional previous method, it has a higher accuracy, better robustness and it is not affected by the camera field of view. In this method, the coincidence error of the corresponding points on the calibration plate after registration is less than 0.1mm.

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