Phase Difference-3D Coordinate Mapping Model of Structural Light Imaging System Based on Extreme Learning Machine Network
To meet the requirements of high accuracy and high efficiency in three-dimensional (3D) measurement, a phase difference-3D coordinate mapping model is proposed based on extreme learning machine (ELM) network. First, the reconstruction model of the ideal measurement system is set following the geomet...
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| Veröffentlicht in: | IEEE access 2020-01, Vol.8, p.1-1 |
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| creator | Lv, Shanshan Jiang, Mingshun Su, Chenhui Zhang, Lei Zhang, Faye Sui, Qingmei Jia, Lei |
| description | To meet the requirements of high accuracy and high efficiency in three-dimensional (3D) measurement, a phase difference-3D coordinate mapping model is proposed based on extreme learning machine (ELM) network. First, the reconstruction model of the ideal measurement system is set following the geometric structure of the system. Subsequently, by generalizing camera and world coordinates, a generalized measurement model is built. Lastly, ELM network is employed to solve the mapping coefficients. During measurement, only one phase difference map is required to complete the 3D reconstruction of the object, which simplifies the data processing process and saves time. The result indicates that the mean square errors (MSEs) of the X, Y and Z of the testing sample are 3.5955×10-4 mm, 9.5113×10-4 mm and 4.4×10-3 mm, respectively. Moreover, the reconstruction experiments of objects with different geometric structures are performed to demonstrate the general application of the proposed method. |
| doi_str_mv | 10.1109/ACCESS.2020.2986225 |
| format | Article |
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Moreover, the reconstruction experiments of objects with different geometric structures are performed to demonstrate the general application of the proposed method.</description><identifier>ISSN: 2169-3536</identifier><identifier>EISSN: 2169-3536</identifier><identifier>DOI: 10.1109/ACCESS.2020.2986225</identifier><identifier>CODEN: IAECCG</identifier><language>eng</language><publisher>Piscataway: IEEE</publisher><subject>3D reconstruction ; Artificial neural networks ; Calibration ; Cameras ; Coordinate measuring machines ; Data processing ; ELM network ; Image reconstruction ; Machine learning ; Mapping ; Neurons ; Phase difference ; Phase measurement ; Phase shift ; structural light ; Three dimensional models ; Three-dimensional displays</subject><ispartof>IEEE access, 2020-01, Vol.8, p.1-1</ispartof><rights>Copyright The Institute of Electrical and Electronics Engineers, Inc. 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| subjects | 3D reconstruction Artificial neural networks Calibration Cameras Coordinate measuring machines Data processing ELM network Image reconstruction Machine learning Mapping Neurons Phase difference Phase measurement Phase shift structural light Three dimensional models Three-dimensional displays |
| title | Phase Difference-3D Coordinate Mapping Model of Structural Light Imaging System Based on Extreme Learning Machine Network |
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