因為傳統雙目相機會受光照變化和物體紋理影響，並且非常依賴圖像特徵匹配，而造成精度不穩，並且成本使用很大，本論文提出基於結構光之3D點雲重建技術並結合結構光編碼，生成適合的結構光圖案，並進行3D點雲提取，此系統利用結構光還原進行3D重建，得到回傳的影像資訊，進行點雲處理。
本論文主軸為建立結構光系統架構以及新編碼與傳統編碼的融合，我們使用TI的DLP技術和CCD攝影機，提升影像間的特徵辨識效率及匹配精度，為了取得結構光深度資訊，利用格雷碼得知三維訊息，並且我們提出了另一種新的圖案設計編碼，利用編碼可以得知物體完整深度訊息，以及可以辨識特殊區域，並將與格雷碼結合，最後還原出三維點雲，再經由點雲特徵提取，利用點雲預處理和點雲分割，先將點雲進行降採樣演算法(Downsampling)把點雲的數量減少，減少迭代次數，接著進行RANSAC演算法，最後完成點雲平面之間的分割，取得所需的三維點雲。
在本論文最後發展傳統結構光編碼和新的提出編碼的結合，利用第一次的新編碼的掃描下來之後得到的訊息，找出變化位置，生成適合的結構光圖案，在進行特點掃描，並取得相關資訊，最後融合傳統結構光編碼，形成三維點雲，實驗結果，比起傳統結構光，使用時間成本高一點，但還原結果相對較高一點，以此驗證本系統是可行性的。

Because traditional binocular cameras are affected by illumination changes and object textures and rely heavily on image feature matching, resulting in unstable accuracy and high cost, this paper proposes 3D point cloud reconstruction technology based on structured light combined with structured light code. A suitable structured light pattern is generated, and 3D point cloud extraction is performed. This system uses structured light restoration to perform 3D reconstruction and obtains the returned image information for point cloud processing.
The main focus of this paper is to establish a structured light system architecture and the integration of new coding and traditional coding. We use TI's DLP technology and CCD camera to improve the feature recognition efficiency and matching accuracy between images. Three-dimensional information is obtained, and we propose another new pattern design code that can use the code to know the complete depth information of the object, identify particular areas, combine with the Gray code, finally restoring the three-dimensional point cloud. Then, through point cloud feature extraction, using point cloud preprocessing and point cloud segmentation, we first perform downsampling on the point cloud to reduce the number of point clouds and the number of iterations, then perform the RANSAC algorithm, and finally complete the point cloud plane. Segmentation is performed to obtain the desired 3D point cloud.
At the end of this paper, the combination of traditional structured light coding and the new proposed coding is developed. The information obtained after the first scanning of the new coding is used to find the change position, generate a suitable structured light pattern, perform characteristic scanning, obtain relevant information, and, finally, integrate the traditional structured light coding to form a three-dimensional point cloud. The experimental results show that the use time cost is slightly higher than that of traditional structured light. Nevertheless, the restoration results are relatively high to verify this system's feasibility.

[1] Young, T. (1804). The Bakerian Lecture: Experiments and Calculations Relative to Physical Optics. Philosophical Transactions of the Royal Society of London, 94, 1–16.
[2] Jason Geng, "Structured-light 3D surface imaging: a tutorial," Adv. Opt. Photon. 3, 128-160 (2011).
[3] Z.H. Zhang, Review of single-shot 3D shape measurement by phase calculation-based fringe projection techniques, Optics and Lasers in Engineering, Volume 50, Issue 8, 2012, Pages 1097-1106.
[4] J. Y. Shieh and L. H. Shyu, " Measurement of 3D Profile Using Encodeed Light Pattern, " 電腦視覺、圖學暨影像處理研討會論文集, pp.392-397, 1997.
[5] Song Zhang, Recent progresses on real-time 3D shape measurement using digital fringe projection techniques, Optics and Lasers in Engineering, Volume 48, Issue 2, 2010, Pages 149-158.
[6] Qican Zhang, Xianyu Su, Liqun Xiang, Xuezhen Sun, 3-D shape measurement based on complementary Gray-code light, Optics and Lasers in Engineering, Volume 50, Issue 4, 2012, Pages 574-579.
[7] Chao Zuo, Shijie Feng, Lei Huang, Tianyang Tao, Wei Yin, Qian Chen, Phase shifting algorithms for fringe projection profilometry: A review, Optics and Lasers in Engineering, Volume 109, 2018, Pages 23-59.
[8] D. Li and S. Liu, "Structured Light Based High Precision 3D Measurement and Workpiece Pose Estimation," 2019 Chinese Automation Congress (CAC), 2019, pp. 669-674.
[9] Z. Lu, J. Fan, Z. Hou, S. Deng, C. Zhou and F. Jing, "Automatic 3D Seam Extraction Method for Welding Robot Based on Monocular Structured Light," in IEEE Sensors Journal, vol. 21, no. 14, pp. 16359-16370, 15 July15, 2021.
[10] Haihua Cui, Tao Jiang, Kunpeng Du, Ronghui Guo, An′an Zhao. 3D Imaging Method for Multi-View Structured Light Measurement Via Deep Learning Pose Estimation[J]. Acta Optica Sinica, 2021, 41(17): 1712001.
[11] M. Maruyama and S. Abe, "Range sensing by projecting multiple slits with random cuts," in IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 15, no. 6, pp. 647-651, June 1993, doi: 10.1109/34.216735.
[12] Minoru Ito, Akira Ishii, “A three-level checkerboard pattern (TCP) projection method for curved surface measurement,” Pattern Recognition, 28 (1), 27 –40 (1995). https://doi.org/10.1016/0031-3203(94)E0047-O Google Scholar
[13] N. G. Durdle, J. Thayyoor and V. J. Raso, "An improved structured light technique for surface reconstruction of the human trunk," Conference Proceedings. IEEE Canadian Conference on Electrical and Computer Engineering (Cat. No.98TH8341), 1998, pp. 874-877 vol.2, doi: 10.1109/CCECE.1998.685637.
[14] Li Zhang, B. Curless and S. M. Seitz, "Rapid shape acquisition using color structured light and multi-pass dynamic programming," Proceedings. First International Symposium on 3D Data Processing Visualization and Transmission, 2002, pp. 24-36, doi: 10.1109/TDPVT.2002.1024035.
[15] P. Vuylsteke, A. Oosterlinck, IEEE Transactions on Pattern Analysis and Machine Intelligence, 12 (2), 148 (1990).
[16] C. Albitar, P. Graebling and C. Doignon, ICIPC 2007, 2007 IEEE International Conference on Image Processing, (6) 529, (2007).
[17] C.C. Lau, C.C. Sun , T.H. Yang, Y.W. Yu, S.M. Chou, Proceeding Current Developments in Lens Design and Optical Engineering XIX, 1074504, (2018).
[18] Y. Guo, H. Wang, Q. Hu, H. Liu, L. Liu and M. Bennamoun, "Deep Learning for 3D Point Clouds: A Survey," in IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 43, no. 12, pp. 4338-4364, 1 Dec. 2021,
[19] B. Zou, H. Qiu and Y. Lu, "Point Cloud Reduction and Denoising Based on Optimized Downsampling and Bilateral Filtering," in IEEE Access, vol. 8, pp. 136316-136326, 2020.
[20] M. Zhong, C. Li, L. Liu, J. Wen, J. Ma and X. Yu, "Fuzzy Neighborhood Learning for Deep 3-D Segmentation of Point Cloud," in IEEE Transactions on Fuzzy Systems, vol. 28, no. 12, pp. 3181-3192, Dec. 2020.
[21] Martin A. Fischler and Robert C. Bolles. 1981. Random sample consensus: a paradigm for model fitting with applications to image analysis and automated cartography. Commun. ACM 24, 6 (June 1981), 381–395.
[22] C. -Y. Tsai and S. -H. Tsai, "Simultaneous 3D Object Recognition and Pose Estimation Based on RGB-D Images," in IEEE Access, vol. 6, pp. 28859-28869, 2018
[23] Schnabel, R., Wahl, R. and Klein, R. (2007), Efficient RANSAC for Point-Cloud Shape Detection. Computer Graphics Forum, 26: 214-226.
[24] C. Tomasi and R. Manduchi, "Bilateral filtering for gray and color images," Sixth International Conference on Computer Vision (IEEE Cat. No.98CH36271), 1998, pp. 839-846
[25] P. Zhou, R. Peng, M. Xu, V. Wu and D. Navarro-Alarcon, "Path Planning With Automatic Seam Extraction Over Point Cloud Models for Robotic Arc Welding," in IEEE Robotics and Automation Letters, vol. 6, no. 3, pp. 5002-5009, July 2021,
[26] Yang Chen, Gérard Medioni, Object modelling by registration of multiple range images, Image and Vision Computing, Volume 10, Issue 3, 1992.
[27] P. J. Besl and N. D. McKay, "A method for registration of 3-D shapes," in IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 14, no. 2, pp. 239-256, Feb. 1992
[28] P. Li, R. Wang, Y. Wang and W. Tao, "Evaluation of the ICP Algorithm in 3D Point Cloud Registration," in IEEE Access, vol. 8, pp. 68030-68048, 2020.
[29] Elahi, J. Lu, Q. -D. Zhu and L. Yong, "A Single-Shot, Pixel Encoded 3D Measurement Technique for Structure Light," in IEEE Access, vol. 8, pp. 127254-127271, 2020, doi: 10.1109/ACCESS.2020.3009025
[30] Chi-Chung Lau, Ching-Cherng Sun, Tsung-Hsun Yang, Yeh-Wei Yu, and Si-Min Chou "Design of coded structured light based on square-shaped primitives", Proc. SPIE 10745, Current Developments in Lens Design and Optical Engineering XIX, 1074504 (17 September 2018)
[31] T. B. Nguyen and C. V. Le, "Symmetrical-symbol pattern based structured light for accurate decoding," 2016 IEEE Sixth International Conference on Communications and Electronics (ICCE), 2016, pp. 315-320, doi: 10.1109/CCE.2016.7562655.
[32] Xiaojun Jia, Zihao Liu, "One-Shot M-Array Pattern Based on Coded Structured Light for Three-Dimensional Object Reconstruction", Journal of Control Science and Engineering, vol. 2021, Article ID 6676704, 16 pages, 2021.
[33] Chen L-C, Liang C-W. Novel Boundary Edge Detection for Accurate 3D Surface Profilometry Using Digital Image Correlation. Applied Sciences. 2018; 8(12):2541. https://doi.org/10.3390/app8122541.
[34] Manh-Trung Le, Liang-Chia Chen, Chih-Jer Lin, Reconstruction of accurate 3-D surfaces with sharp edges using digital structured light projection and multi-dimensional image fusion, Optics and Lasers in Engineering, Volume 96, 2017, P 17-34, https://doi.org/10.1016/j.optlaseng.2017.04.002
[35] Chen L-C, Hoang D-C, Lin H-I, Nguyen T-H. Innovative Methodology for Multi-View Point Cloud Registration in Robotic 3D Object Scanning and Reconstruction. Applied Sciences. 2016; 6(5):132. https://doi.org/10.3390/app6050132
[36] Dinh-Cuong Hoang, Liang-Chia Chen1, and Thanh-Hung Nguyen, "Sub-OBB based object recognition and localization algorithm using range images," Measurement Science and Technology, Volume 28, Number 2, p 025401 , 29 December 2016.
[37] Liang-Chia Chen and Dinh-Cuong Hoang and Hsien-I Lin and Thanh-Hung Nguyen, "A 3-D point clouds scanning and registration methodology for automatic object digitization", Smart Science, vol. 4, no. 1 ,p1-7, 2016. doi : 10.1080/23080477.2016.1145459.
[38] Liang-Chia Chen and Nguyen Van Thai and Hung-Fa Shyu and Hsien-I Lin, " In situ clouds-powered 3-D radiation detection and localization using novel color-depth-radiation (CDR) mapping," Advanced Robotics , vol. 28, no. 12 ,p 841-857, 2014. doi : 10.1080/01691864.2014.894942.
[39] Liang-Chia Chen, Hoang Hong Hai, " Fourier transform profilometry employing novel orthogonal elliptic band-pass filtering for accurate 3-D surface reconstruction Precision Engineering, Volume 38, Issue 3, 2014, Pages 512-524, https://doi.org/10.1016/j.precisioneng.2014.01.006.
[40] Liang-Chia Chen, Thanh-Hung Nguyen and Shyh-Tsong Lin, , "Viewpoint-independent 3D object segmentation for randomly stacked objects using optical object detection," Measurement Science and Technology, Volume 26, Number 10,p 105202, 15 September 2015.
[41] U. Wijenayake, S. Choi and S. Park, "Combination of Color and Binary Pattern Codification for an Error Correcting M-array Technique," 2012 Ninth Conference on Computer and Robot Vision, 2012, pp. 139-146, doi: 10.1109/CRV.2012.26.