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3D shape measurement based on structured light field imaging

  • Received: 30 April 2019 Accepted: 29 August 2019 Published: 22 October 2019
  • In this paper, a three-dimensional (3D) shape measurement method based on structured light field imaging is proposed, which contributes to the biomedical imaging. Generally, light field imaging is challenging to accomplish the 3D shape measurement accurately, as the slope estimation method based on radiance consistency is inaccurate. Taking into consideration the special modulation of structured light field, we utilize the phase information to substitute the phase consistency for the radiance consistency in epi-polar image (EPI) at first. Therefore, the 3D coordinates are derived after light field calibration, but the results are coarse due to slope estimation error and need to be corrected. Furthermore, the 3D coordinates refinement is performed based on relationship between the structured light field image and DMD image of the projector, which allows to improve the performance of the 3D shape measurement. The necessary light field camera calibration is described to generalize its application. Subsequently, the effectiveness of the proposed method is demonstrated with a sculpture and compared to the results of a conventional PMP system.

    Citation: Ping Zhou, Yuting Zhang, Yunlei Yu, Weijia Cai, Guangquan Zhou. 3D shape measurement based on structured light field imaging[J]. Mathematical Biosciences and Engineering, 2020, 17(1): 654-668. doi: 10.3934/mbe.2020034

    Related Papers:

  • In this paper, a three-dimensional (3D) shape measurement method based on structured light field imaging is proposed, which contributes to the biomedical imaging. Generally, light field imaging is challenging to accomplish the 3D shape measurement accurately, as the slope estimation method based on radiance consistency is inaccurate. Taking into consideration the special modulation of structured light field, we utilize the phase information to substitute the phase consistency for the radiance consistency in epi-polar image (EPI) at first. Therefore, the 3D coordinates are derived after light field calibration, but the results are coarse due to slope estimation error and need to be corrected. Furthermore, the 3D coordinates refinement is performed based on relationship between the structured light field image and DMD image of the projector, which allows to improve the performance of the 3D shape measurement. The necessary light field camera calibration is described to generalize its application. Subsequently, the effectiveness of the proposed method is demonstrated with a sculpture and compared to the results of a conventional PMP system.


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    [1] S. V. der Jeughtand and J. J. J. Dirckx, Real-time structured light profilometry: A review, Opt. Lasers Eng., 87(2016), 18-31.
    [2] M. Levoy, R. Ng, A. Adams, et al., Light field microscopy, ACM Trans. Graphics, 25 (2006), 924-934.
    [3] Y. D. Sie, C. Y. Lin and S. J. Chen, 3D surface morphology imaging of opaque microstructures via light-field microscopy, Sci. Rep., 8 (2018), 10505.
    [4] J. Liu, D. Claus, T. Xu, et al., Light field endoscopy and its parametric description, Opt. Lett., 42 (2017), 1804-1807.
    [5] X. Lin, J. Wu, G. Zheng, et al., Camera array based light field microscopy, Biomed. Opt. Express, 6 (2015), 3179-3189.
    [6] E. H. Adelson and J. Y. A. Wang, Single lens stereo with a plenoptic camera, IEEE Trans. Pattern Anal., 14 (1992), 99-106.
    [7] R. Ng, M. Levoy, M. Bredif, et al., Light field photography with a hand-held plenoptic camera, Comput. Sci. Tech. Rep., 2 (2005), 1-11.
    [8] C. Hahne, A. Aggoun, V. Velisavljevic, et al., Refocusing distance of a standard plenoptic camera, Opt. Express, 24 (2016), 21521-21540.
    [9] M. T. Tao, S. Hadap, J. Malik, et al., Depth from combining defocus and correspondence using light-field cameras, Proceedings of IEEE International Conference on Computer Vision (2013), 673-680. Available from: https://www.cv-foundation.org/openaccess/content_iccv_2013/html/Tao_Depth_from_Combining_2013_ICCV_paper.html.
    [10] A. Criminisi, S. B. Kang, R. Swaminathan, et al., Extracting layers and analyzing their specular properties using epipolar-plane-image analysis, Comput. Vision Image Understanding, 97 (2005), 51-58.
    [11] C. Kim, H. Zimmer, Y. Pritch, et al., Scene reconstruction from high spatio-angular resolution light fields, ACM Trans. Graphics, 32 (2013), 73-1.
    [12] S. Wanner and B. Goldluecke, Globally consistent depth labeling of 4D light fields, 2012 IEEE Conference on Computer Vision and Pattern Recognition, 41-48. Available from: https://ieeexplore_ieee.gg363.site/abstract/document/6247656.
    [13] M. Diebold, B. Jaehne and A. Gatto, Heterogeneous light fields, 2016 IEEE Conference on Computer Vision and Pattern Recognition, 1745-1753. Available from: https://ieeexplore_ieee.gg363.site/abstract/document/7780562.
    [14] P. Yang, Z. Wang, Y. Yan, et al., Close-range photogrammetry with light field camera: From disparity map to absolute distance, Appl. Opt., 55 (2016), 7477-7486.
    [15] Z. Zhang, A flexible new technique for camera calibration, IEEE Trans. Pattern Anal. Mach. Intell., 22 (2000), 1330-1334.
    [16] P. Zhou, W. Cai, Y. Yu, et al., A two-step calibration method of lenslet-based light field cameras, Opt. Lasers Eng., 115 (2019), 190-196.
    [17] D. G. Dansereau, O. Pizarro and S. B. Williams, Decoding, calibration and rectification for lenselet-based plenoptic cameras, IEEE Conference on Computer Vision and Pattern Recognition (2013), 1027-1034. Available from: https://www.cv-foundation.org/openaccess/content_cvpr_2013/html/Dansereau_Decoding_Calibration_and_2013_CVPR_paper.html.
    [18] S. Zhang and P. S. Huang, Novel method for structured light system calibration, Opt. Eng., 45 (2006), 083601.
    [19] C. Zuo, L. Huang, M. Zhang, et al., Temporal phase unwrapping algorithms for fringe projection profilometry: A comparative review, Opt. Lasers Eng., 85 (2016), 84-103.
    [20] H. G. Jeon, J. Park, G. Choe, et al., Accurate depth map estimation from a lenslet light field camera, Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, 2015, 1547-1555. Available from: http://openaccess.thecvf.com/content_cvpr_2015/html/Jeon_Accurate_Depth_Map_2015_CVPR_paper.html.
    [21] J. Yi and S. Huang, Modified Fourier transform profilometry for the measurement of 3D steep shapes, Opt. Lasers Eng., 27 (1997), 493-505.
    [22] P. Zhou, Y. Yu, W. Cai, et al., Non-iterative three dimensional reconstruction method of the structured light system based on polynomial distortion representation, Opt. Lasers Eng., 100 (2018), 216-225.
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