Volume 1 Issue 2
Apr.  2021
Turn off MathJax
Article Contents
Pan ZHANG, Zhong KAI, Zhongwei LI, Xiaobo JIN, Bin LI, Congjun WANG, Yusheng SHI. High dynamic range 3D measurement based on structured light: A review[J]. Journal of Advanced Manufacturing Science and Technology , 2021, 1(2): 2021004. doi: 10.51393/j.jamst.2021004
Citation: Pan ZHANG, Zhong KAI, Zhongwei LI, Xiaobo JIN, Bin LI, Congjun WANG, Yusheng SHI. High dynamic range 3D measurement based on structured light: A review[J]. Journal of Advanced Manufacturing Science and Technology , 2021, 1(2): 2021004. doi: 10.51393/j.jamst.2021004

High dynamic range 3D measurement based on structured light: A review

doi: 10.51393/j.jamst.2021004

This study was co-supported by the National Key Research and Development Program of China (No. 2018YFB1105800), Excellent Young Program of Natural Science Foundation in Hubei Province (No. 2019CFA045), Key Research and Development Program of Hubei Province (No. 2020BAB137) and the Major Project of Technological Innovation in Hubei Province (No. 2019AAA008).

  • Received Date: 2021-02-05
  • Rev Recd Date: 2021-02-22
  • Available Online: 2021-03-13
  • Publish Date: 2021-03-13
  • Structured light method is one of the best methods for automated 3D measurement in industrial production due to its stability and speed. However, when the surface of industrial parts has high dynamic range (HDR) areas, e.g. rust, oil stains, or shiny surfaces, phase calculation errors may happen due to low modulation and pixel over-saturation in the image, making it difficult to obtain accurate 3D data. This paper classifies and summarizes the existing high dynamic range structured light 3D measurement technologies, compares the advantages and analyzes the future development trends. The existing methods are classified into multiple measurement fusion (MMF) and single best measurement (SBM) based on the measurement principle. Then, the advantages of the various methods in the two categories are discussed in detail, and the applicable scenarios are analyzed. Finally, the development trend of high dynamic range 3D measurement based on structed light is proposed.

  • loading
  • [1]
    . Xu J,Zhang S. Status,challenges,and future perspectives of fringe projection profilometry. Optics and Lasers in Engineering. 2020;135:106193.
    . Song L,Li X,Yang Y et al. Structured-light based 3D reconstruction system for cultural relic packaging. Sensors. 2018;18(9):2981.
    . Zhan G,Han L,Li Z,et al. Identification and documentation of auricle defects using three-dimensional optical measurements. Scientific Reports. 2018;8(1):1-7.
    . Zhan G,Tang H,Zhong K,et al. High-speed FPGAbased phase measuring profilometry architecture. Optics express. 2017;25(9):10553-64.
    . Han L,Li Z,Zhong K,et al. Vibration detection and motion compensation for multi-frequency phaseshifting-based 3d sensors. Sensors. 2019;19(6):1368.
    . Wang G,Li W,Jiang C,et al. Simultaneous calibration of multicoordinates for a dual-robot system by solving the AXB=YCZ problem. IEEE Transactions on Robotics. 2021:1-14.
    . Xie H,Li W,Zhu D,et al. A Systematic model of machining error reduction in robotic grinding. IEEE/ASME Transactions on Mechatronics. 2020;25(6):2961-72.
    . Li Z,Liu X,Wen S,et al. In situ 3D monitoring of geometric signatures in the powder-bed-fusion additive manufacturing process via vision sensing methods. Sensors. 2018;18(4):1180.
    . Han L,Cheng X,Li Z,et al. A robot-driven 3D shape measurement system for automatic quality inspection of thermal objects on a forging production line. Sensors. 2018;18(12):4368.
    . Hocken RJ,Pereira PH. Coordinate measuring machines and systems:Second edition. CRC press; 2016. p. 1-565.
    . Liu SG,Peng K,Huang FS,et al. A portable 3D vision coordinate measurement system using a light pen. Key Engineering Materials. 2005;295-296:3316.
    . Shi B,Liang J. Guide to quickly build high-quality three-dimensional models with a structured light range scanner. Applied optics. 2016;55(36):1015869.
    . Slizewski A,Semal P. Experiences with low and high cost 3D surface scanner. Quartär. 2009;56:1318.
    . Jing W,Goh CF,Rajaraman M,et al. A computational framework for automatic online path generation of robotic inspection tasks via coverage planning and reinforcement learning. IEEE Access. 2018;6:54854-64.
    . Lartigue C,Quinsat Y,Mehdi-Souzani C,et al. Voxel-based path planning for 3D scanning of mechanical parts. Computer-Aided Design and Applications. 2014;11(2):220-7.
    . Germani M,Mandorli F,Mengoni M,et al. CADbased environment to bridge the gap between product design and tolerance control. Precision Engineering. 2010;34(1):7-15.
    . Chen SY,Li YF. Automatic sensor placement for model-based robot vision. IEEE Transactions on Systems,Man,and Cybernetics,Part B(Cybernetics). 2004;34(1):393-408.
    . Cheng X,Liu X,Li Z,et al. High-accuracy globally consistent surface reconstruction using fringe projection profilometry. Sensors. 2019;19(3):668.
    . He W,Zhong K,Li Z,et al. Accurate calibration method for blade 3D shape metrology system integrated by fringe projection profilometry and conoscopic holography. Optics and Lasers in Engineering. 2018;110:253-61.
    . Salvi J,Fernandez S,Pribanic T,et al. A state of the art in structured light patterns for surface profilometry. Pattern Recognition. 2010;43(8):2666-80.
    . Zhang S,Yau S. High dynamic range scanning technique. Optical Engineering. 2009;48(3):033604.
    . Jiang H,Zhao H,Li X. High dynamic range fringe acquisition:A novel 3-D scanning technique for high-reflective surfaces. Optics and Lasers in Engineering. 2012;50(10):1484-93.
    . Feng S,Zhang Y,Chen Q,et al. General solution for high dynamic range three-dimensional shape measurement using the fringe projection technique. Optics and Lasers in Engineering. 2014;59:56-71.
    . Rao L,Da F. High dynamic range 3D shape determination based on automatic exposure selection. Journal of Visual Communication and Image Representation. 2018;50:217-26.
    . Zhang S. Rapid and automatic optimal exposure control for digital fringe projection technique. Optics and Lasers in Engineering. 2020;128:106029.
    . Liu GH,Liu XY,Feng QY. 3D shape measurement of objects with high dynamic range of surface reflectivity. Applied Optics. 2011;50(23):4557-65.
    . Zhao H,Liang X,Diao X,et al. Rapid in-situ 3D measurement of shiny object based on fast and high dynamic range digital fringe projector. Optics and Lasers in Engineering. 2014;54:170-4.
    . Suresh V,Wang Y,Li B. High-dynamic-range 3D shape measurement utilizing the transitioning state of digital micromirror device. Optics and Lasers in Engineering. 2018;107:176-81.
    . Geng J. DLP-based structured light 3D imaging technologies and applications. SPIE Proceedings 2011;7932:873125.
    . Lei S,Zhang S. Flexible 3-D shape measurement using projector defocusing. Optics letters. 2009;34(20):3080-2.
    . Zhang L,Chen Q,Zuo C,et al. Real-time high dynamic range 3D measurement using fringe projection. Optics Express. 2020;28(17):24363.
    . Wang J,Zhou Y,Yang Y. A novel and fast threedimensional measurement technology for the objects surface with non-uniform reflection. Results in Physics. 2020;16:102878.
    . Waddington C,Kofman J. Saturation avoidance by adaptive fringe projection in phase-shifting 3D surface-shape measurement. 2010 International Symposium on Optomechatronic Technologies. 2010.
    . Waddington C,Kofman J. Camera-independent saturation avoidance in measuring high-reflectivityvariation surfaces using pixel-wise composed images from projected patterns of different maximum gray level. Optics Communications. 2014;333:32-7.
    . Sheng H,Xu J,Zhang S. Dynamic projection theory for fringe projection profilometry. Applied optics 2017;56(30):8452-60.
    . Zhang L,Chen Q,Zuo C,et al. High dynamic range 3D shape measurement based on the intensity response function of a camera. Appl Opt. 2018;57(6):1378-86.
    . Chen T,Lensch HPA,Fuchs C,et al. Polarization and phase-shifting for 3D scanning of translucent objects. Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition. 2007.
    . Li F,Liu J,Cai J. Shape measuring of mirror object based on structured light method. Chinese Journal of Electron Devices. 2014;37(5):882-6.
    . Jiang C,Bell T,Zhang S. High dynamic range realtime 3D shape measurement. Optics Express. 2016;24(7):7337-46.
    . Wang M,Du G,Zhou C,et al. Enhanced high dynamic range 3D shape measurement based on generalized phase-shifting algorithm. Optics Communications. 2017;385:43-53.
    . Yin Y,Cai Z,Jiang H,et al. High dynamic range imaging for fringe projection profilometry with single-shot raw data of the color camera. Optics and Lasers in Engineering. 2017;89:138-44.
    . Zheng Y,Wang Y,Suresh V,et al. Real-time highdynamic-range fringe acquisition for 3D shape measurement with a RGB camera. Measurement Science and Technology. 2019;30(7):075202.
    . Song Z,Jiang H,Lin H,et al. A high dynamic range structured light means for the 3D measurement of specular surface. Optics and Lasers in Engineering. 2017;95:8-16.
    . Waddington C,Kofman J. Analysis of measurement sensitivity to illuminance and fringe-pattern gray levels for fringe-pattern projection adaptive to ambient lighting. Optics and Lasers in Engineering. 2010;48(2):251-6.
    . Waddington CJ,Kofman JD. Modified sinusoidal fringe-pattern projection for variable illuminance in phase-shifting three-dimensional surface-shape metrology. Optical Engineering. 2014;53(8):084109.
    . Lin H,Gao J,Mei Q,et al. Adaptive digital fringe projection technique for high dynamic range threedimensional shape measurement. Optics Express. 2016;24(7):7703-18.
    . Li S,Da F,Rao L. Adaptive fringe projection technique for high-dynamic range three-dimensional shape measurement using binary search. Optical Engineering. 2017;56(9):094111.
    . Chen C,Gao N,Wang X,et al. Adaptive pixel-topixel projection intensity adjustment for measuring a shiny surface using orthogonal color fringe pattern projection. Measurement Science and Technology. 2018;29(5):055203.
    . Chen C,Gao N,Wang X,et al. Adaptive projection intensity adjustment for avoiding saturation in threedimensional shape measurement. Optics Communications. 2018;410:694-702.
    . Yu C,Ji F,Xue J,et al. Adaptive binocular fringe dynamic projection method for high dynamic range measurement. Sensors. 2019;19(18):4023.
    . Liu Y,Fu Y,Cai X,et al. A novel high dynamic range 3D measurement method based on adaptive fringe projection technique. Optics and Lasers in Engineering. 2020;128:106004.
    . Xu F,Zhang Y,Zhang L. An effective framework for 3D shape measurement of specular surface based on the dichromatic reflection model. Optics Communications. 2020;475:126210.
    . Men K,Boimel P,Janopaul-Naylor J,et al. Cascaded atrous convolution and spatial pyramid pooling for more accurate tumor target segmentation for rectal cancer radiotherapy. Phys Med Biol. 2018;63(18):185016.
    . Chen L,Zhu Y,Papandreou G,et al. Encoder-decoder with atrous separable convolution for semantic image segmentation. Proceedings of the European Conference on Computer Vision(ECCV). 2018.
    . Badrinarayanan V,Kendall A,Cipolla R. SegNet:A deep convolutional encoder-decoder architecture for image segmentation. IEEE Transactions on Pattern Analysis and Machine Intelligence. 2017;39(12):2481-95.
    . Chen LC,Papandreou G,Schroff F,et al. Rethinking atrous convolution for semantic image segmentation. arXiv:1706.05587.2017;abs/1706.05587.
    . Chen L,Papandreou G,Kokkinos I,et al. Deeplab:Semantic image segmentation with deep convolutional nets,atrous convolution,and fully connected crfs. IEEE Transactions on Pattern analysis and Machine Intelligence. 2018;40(4):834-48.
    . Yu F,Koltun V. Multi-scale context aggregation by dilated convolutions. arXiv preprint arXiv:1511.07122.2015.
    . Chen L,Papandreou G,Kokkinos I,et al. Semantic image segmentation with deep convolutional nets and fully connected crfs. arXiv preprint arXiv:1412.7062.2014.
    . Liu X,Chen W,Madhusudanan H,et al. Optical measurement of highly reflective surfaces from a single exposure. IEEE Transactions on Industrial Informatics. 2021;17(3):1882-91.
    . Liu Y,Fu Y,Zhuan Y,et al. High dynamic range real-time 3D measurement based on Fourier transform profilometry. Optics&Laser Technology. 2021;138:106833.
    . Zhang L,Chen Q,Zuo C,et al. High-speed high dynamic range 3D shape measurement based on deep learning. Optics and Lasers in Engineering. 2020;134:106245.
    . Yu H,Zheng D,Fu J,et al. Deep learning-based fringe modulation-enhancing method for accurate fringe projection profilometry. Optics Express. 2020;28(15):21692-703.
    . Nguyen H,Wang Y,Wang Z. Single-shot 3d shape reconstruction using structured light and deep convolutional neural networks. Sensors. 2020;20(13):3718.
    . Law W,Lun DP. Deep learning based period order detection in structured light three-dimensional scanning. 2019 IEEE International Symposium on Circuits and Systems(ISCAS). 2019.
    . Van der Jeught S,Dirckx JJ. Deep neural networks for single shot structured light profilometry. Optics express. 2019;27(12):17091-101.
    . Li F,Li Q,Zhang T,et al. Depth acquisition with the combination of structured light and deep learning stereo matching. Signal Processing:Image Communication. 2019;75:111-7.
    . Ekstrand L,Zhang S. Autoexposure for three-dimensional shape measurement using a digital-light-processing projector. Optical Engineering. 2011;50(12):123603.
    . Zhong K,Li Z,Zhou X,et al. Enhanced phase measurement profilometry for industrial 3D inspection automation. The International Journal of Advanced Manufacturing Technology. 2015;76(9-12):1563-74.
    . Chen B, Zhang S. High-quality 3D shape measurement using saturated fringe patterns. Optics and Lasers in Engineering. 2016;87:83-9.
    . Feng S, Chen Q, Zuo C, et al. Fast three-dimensional measurements for dynamic scenes with shiny surfaces. Optics Communications. 2017;382:18-27.
    . Hu Y, Chen Q, Liang Y, et al. Microscopic 3D measurement of shiny surfaces based on a multi-frequency phase-shifting scheme. Optics and Lasers in Engineering. 2019;122:1-7.
  • 加载中


    通讯作者: 陈斌, bchen63@163.com
    • 1. 

      沈阳化工大学材料科学与工程学院 沈阳 110142

    1. 本站搜索
    2. 百度学术搜索
    3. 万方数据库搜索
    4. CNKI搜索


    Article Metrics

    Article views (1509) PDF downloads(236) Cited by()
    Proportional views


    DownLoad:  Full-Size Img  PowerPoint