
Proceedings Paper
A new 3D shape precision measurement system calibration method based on non-diffraction grating structured light projectionFormat | Member Price | Non-Member Price |
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Paper Abstract
Phase calculation-based fringe projection techniques are widely used in three-dimensional shape measurement fields to obtain the 3D shape data of the object’s surface. One important step of the phase calculation is calibration, which determines the relationship between the image phase and depth information. The traditional calibration methods are too complex and require many parameters. In this paper, model of 3D shape precision calibration method based on non-diffraction grating structured light fringes projection is proposed, which is consist of camera model, fringe phase obtaining, height-phase relationship model. This method is simple, convenient and there is no approximation in it, which can satisfy the precision measurement.
Paper Details
Date Published: 2 March 2016
PDF: 6 pages
Proc. SPIE 9901, 2nd ISPRS International Conference on Computer Vision in Remote Sensing (CVRS 2015), 99011A (2 March 2016); doi: 10.1117/12.2234788
Published in SPIE Proceedings Vol. 9901:
2nd ISPRS International Conference on Computer Vision in Remote Sensing (CVRS 2015)
Cheng Wang; Rongrong Ji; Chenglu Wen, Editor(s)
PDF: 6 pages
Proc. SPIE 9901, 2nd ISPRS International Conference on Computer Vision in Remote Sensing (CVRS 2015), 99011A (2 March 2016); doi: 10.1117/12.2234788
Show Author Affiliations
Ya Zhu, Huazhong Univ. of Science and Technology (China)
Liping Zhou, Huazhong Univ. of Science and Technology (China)
Wenlong Li, Huazhong Univ. of Science and Technology (China)
Liping Zhou, Huazhong Univ. of Science and Technology (China)
Wenlong Li, Huazhong Univ. of Science and Technology (China)
Jianghong Gan, Huazhong Univ. of Science and Technology (China)
Long Xu, Huazhong Univ. of Science and Technology (China)
Long Xu, Huazhong Univ. of Science and Technology (China)
Published in SPIE Proceedings Vol. 9901:
2nd ISPRS International Conference on Computer Vision in Remote Sensing (CVRS 2015)
Cheng Wang; Rongrong Ji; Chenglu Wen, Editor(s)
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