Browse > Article
http://dx.doi.org/10.3807/COPP.2018.2.6.554

Development of Color 3D Scanner Using Laser Structured-light Imaging Method  

Ko, Youngjun (Department of Electrical and Information Engineering, Seoul National University of Science and Technology)
Yi, Sooyeong (Department of Electrical and Information Engineering, Seoul National University of Science and Technology)
Publication Information
Current Optics and Photonics / v.2, no.6, 2018 , pp. 554-562 More about this Journal
Abstract
This study presents a color 3D scanner based on the laser structured-light imaging method that can simultaneously acquire 3D shape data and color of a target object using a single camera. The 3D data acquisition of the scanner is based on the structured-light imaging method, and the color data is obtained from a natural color image. Because both the laser image and the color image are acquired by the same camera, it is efficient to obtain the 3D data and the color data of a pixel by avoiding the complicated correspondence algorithm. In addition to the 3D data, the color data is helpful for enhancing the realism of an object model. The proposed scanner consists of two line lasers, a color camera, and a rotation table. The line lasers are deployed at either side of the camera to eliminate shadow areas of a target object. This study addresses the calibration methods for the parameters of the camera, the plane equations covered by the line lasers, and the center of the rotation table. Experimental results demonstrate the performance in terms of accurate color and 3D data acquisition in this study.
Keywords
Color 3D scanner; Rotation table; Structured-light; Line laser; Calibration;
Citations & Related Records
연도 인용수 순위
  • Reference
1 L. Chen and C. Huang, "Miniaturized 3D surface profilometer using digital fringe projection," Meas. Sci. Technol. 16, 1061-1068 (2005).   DOI
2 J. Sturm, E. Bylow, F. Kahl, and D. Cremers, "CopyMe3D: scanning and printing persons in 3D," in Proc. of German Conference on Pattern Recognition (Germany, Sept. 2013), pp. 405-414.
3 F. Lilley, M. Lalor, and D. Burton, "Robust fringe analysis system for human body shape measurement," Opt. Eng. 39, 187-195 (2000).   DOI
4 J. Moigne and A. Waxman, "Structured light patterns for robot mobility," IEEE J. Rob. Autom. 4, 541-548 (1988).   DOI
5 J. Shen and N. Gans, "Robot-to-human feedback and automatic object grasping using an RGB-D camera-projector system," Robotica, Cambridge University Press (2017).
6 C. Wieghardt and B. Wagner, "Self-calibration of a mobile manipulator using structured light," in Proc. of IEEE International Conference on Advanced Robotics (ICAR) (China, Jul. 2017), pp. 197-203.
7 M. Levoy, K. Pulli, B. Curless, S. Rusinkiewicz, D. Koller, L. Pereira, M. Ginzton, S. Anderson, J. Davis, J. Ginsberg, J. Shade, and D. Fulk, "The digital michelangelo project: 3D scanning of large statues," in Proc. of 27th Annual Conference on Computer Graphics and Interactive Techniques (SIGGRAPH'00) (Jul. 2000), pp. 131-144.
8 S. Zhang, "Recent progresses on real-time 3D shape measurement using digital fringe projection techniques," Opt. Lasers. Eng. 48, 149-158 (2010).   DOI
9 S. Gorthi and P. Rastogi, "Fringe projection techniques: Whither we are?," Opt. Lasers Eng. 48, 133-140 (2010).   DOI
10 J. Posdamer and M. Altschuler, "Surface measurement by space encoded projected beam system," Comput. Graphics Image Process. 18, 1-17 (1982).   DOI
11 G. Pavlidis, A. Koutsoudis, F. Arnaoutoglou, V. Tsioukas, and C. Chamzas, "Methods for 3D digitization of cultural heritage," J. Cult. Heritage 8, 93-98 (2007).   DOI
12 S. Tang, X. Zhang, Z. Song, L. Song, and H. Zeng, "Robust pattern decoding in shape-coded structured light," Opt. Lasers Eng. 96, 50-62 (2017).   DOI
13 D. Scharstein and R. Szeliski, "High accuracy stereo depth maps using structured light," in Proc. IEEE Conference on Computer Vision and Pattern Recognition (USA, Jun. 2003), pp. 195-202.
14 A. Boyer and P. Payeur, "Enhancing structured light range imaging by adaptation of color, exposure and focus," in Proc. IEEE International Conference on Computational Intelligence and Virtual Environments for Measurement Systems and Applications (CIVEMSA) (France, Jun. 2017).
15 K. Liu, Y. Wang, D. Lau, Q. Hao, and L. Hassebrook, "Dual-frequency pattern scheme for high-speed 3-D shape measurement," Opt. Express 18, 5229-5244 (2010).   DOI
16 C. Jiang, T. Bell, and S. Zhang, "High dynamic range realtime 3D shape measurement," Opt. Express 24, 7337 (2016).   DOI
17 J. Salvi, J. Pages, and J. Batlle, "Pattern codification strategies in structured light systems," Pattern Recognit. 37, 827-849 (2004).   DOI
18 Z. Zhang and L. Yuan, "Building a 3D scanner system based on monocular vision," Appl. Opt. 51, 1638-1644 (2012).   DOI
19 J. Franca, M. Gazziro, A. Ide, and J. Saito, "A 3D scanning system based on laser triangulation and variable field of view", in Proc. IEEE International Conference on Image Processing (Italy, Sept. 2005), pp. 425-428.
20 O. Fleischmann and R. Koch, "Fast projector-camera calibration for interactive projection mapping," in Proc. of International Conference on Pattern Recognition (ICPR) (Mexico, Dec. 2016), pp. 3798-3803.
21 S. Zhang and P. Huang, "Novel method for structured light system calibration," Opt. Eng. 45, 083601-083608 (2006).   DOI
22 M. Kazhdan, M. Bolitho, and H. Hoppe, "Poisson surface reconstruction," Eurographics Symposium on Geometry Processing (2006).
23 D. P. Bertsekas, "Constrained optimization and lagrange multiplier methods," Academic Press, New York (2014).
24 https://matterandform.net/scanner.
25 https://www.artec3d.com/files/pdf/ArtecScanners-Booklet-EU RO.pdf.
26 J. Han, L. Shao, D. Xu, and J. Shotton, "Enhanced computer vision with microsoft kinect sensor: a review," IEEE Trans. Cybern. 43, 1318-1334 (2013).   DOI
27 F. Alhwarin, A. Ferrein, and I. Scholl, "IR stereo kinect: improving depth images by combining structured light with IR stereo," Lect. Notes Comput. Sci. 8862, 409-421 (2014).
28 G. Taubin and D. Moreno, "Build your own desktop 3D scanner," SIGGRAPH2014, 28-38 (2014).
29 J. Beraldin, F. Blais, L. Cournoyer, G. Godin, and M. Rioux, "Active 3D sensing," NRC Tech. Rep. 44159, Ottawa (2000).
30 L. Zhang, H. Dong, and A. Saddik, "From 3D sensing to printing: a survey," ACM Trans. Multimedia Comput., Commun., Appl. 12, 1-24 (2016).
31 A. Weckenmann. G. Peggs, and J. Hoffmann, "Probing systems for dimensional micro- and nano-metrology," Meas. Sci. Technol. 17, 504-509 (2006).   DOI
32 R. Jain, R. Kasturi, and B. G. Schunck, Machine vision, McGraw-Hill (1995).
33 S. Rusinkiewicz, O. Hall-Holt, and M. Levoy, "Real-time 3D model acquisition," SIGGRAPH (2002).
34 G. Liu, X. Liu, and Q. Feng, "3D shape measurement of objects with high dynamic range of surface reflectivity," Appl. Opt. 50, 4557-4565 (2011).   DOI
35 C. Rocchini, P. Cignoni, C. Montani, P. Pingi, and R. Scopigno, "A low cost 3D scanner based on structured light," Comput. Graphics Forum 20, 299-308 (2001).   DOI
36 F. Buonamici, M. Carfagni, and Y. Volpe, "Recent strategies for 3D reconstruction using reverse engineering: a bird's eye view," Adv. Mech., Des. Eng. Manuf. 841-850 (2017).