Applying a statistical constraint to the 3D reconstruction of the un-textured surface's cross-sections using a structured light system consists of two cameras and a planer laser

Document Type : Persian Original Article

Authors

Department of Geodesy and Surveying Engineering, Tafresh University, Tafresh, Iran

Abstract

In this paper, a simple structured light system is designed to produce the three-dimensional points cloud from the un-textured surfaces. The system consists of two cameras and a planer laser, in which the 3D contents are produced through the stereo images taken from the light reflected by the intersection of a planer laser and the 3D surface of an object. There was no control over how the laser swept through the surface and the instantaneous parameters of the laser plane were not known in advance. Considering the knowledge of the internal camera calibration parameters and the relative orientation of the stereo-pairs, the video captured by the cameras are normalized during the epipolar re-sampling process. Next, in each pair of simultaneous frames, the matched points located at the 3D section of the laser’s plane are then identified. During the simultaneous space intersection of the matched points, a constraint is applied to enforce the singularity of the covariance matrix of 3D points lie in the intersection of the laser's plane and the 3D surface of an object to ensure their co-planarity. By applying this statistical constraint, the precision of the surface 3D reconstruction was improved up to 41% in this structured light system.

Keywords

References

[1]   S. Hadiyoso, G. T. Musaharpa, and I. Wijayanto, "Prototype implementation of dual laser 3D scanner system using cloud to cloud merging method," in 2017 IEEE Asia Pacific Conference on Wireless and Mobile (APWiMob), 2017, pp. 36-40: IEEE.
[2]   T. T. Nguyen, Q. M. Nguyen, X. G. Liu, and Y. Y. Ziggah, "3D object model reconstruction based on laser scanning point cloud data," in Int. Symp. Geoinformatics Spat. Infrastruct. Dev. Earth Allied Sci, 2012.
[3]   S. Winkelbach, S. Molkenstruck, and F. M. Wahl, "Low-cost laser range scanner and fast surface registration approach," in Joint Pattern Recognition Symposium, 2006, pp. 718-728: Springer.
[4]  علی ابذل،مسعود ورشوساز، محمد سعادت سرشت "مدلسازی سه­بعدیاز طریق تاباندن خطوط لیزر متقاطع"، دهمین همایش ملی ژئوماتیک،اردیبهشت، تهران، 1389.
[5]  اکبر جعفری،فرهاد صمدزادگان،محمد سعادت سرشت، حسن امامی "مدلسازی سه­بعدی اشیاء با بافت یکسان و بدون تارگت­گذاری با استفاده از روش نور ساخت یافته : طراحی، ساخت و ارزیابی"، نشریه علمی- ترویجی مهندسی نقشه برداری اطلاعات مکانی، دوره هشتم شماره دو، 1396
[6]   Z. Xiong and Y. Zhang, "A critical review of image registration methods," International Journal of Image and Data Fusion, vol. 1, no. 2, pp. 137-158, 2010.
[7]   J. Salvi, J. Pages, and J. Batlle, "Pattern codification strategies in structured light systems," Pattern recognition, vol. 37, no. 4, pp. 827-849, 2004.
[8]   C. B, J. Y, Zhang;, and R. J, Zhang, "Improving the accuracy of stripe center extraction in a structured light measurement system," Natural Foundation Research Project of Shaanxi Province, 2019.
[9]   J. van der Lucht, M. Bleier, F. Leutert, K. Schilling, and A. Nüchter, "STRUCTURED-LIGHT BASED 3D LASER SCANNING OF SEMI-SUBMERGED STRUCTURES," ISPRS Annals of Photogrammetry, Remote Sensing & Spatial Information Sciences, vol. 4, no. 2, 2018.
[10] Z. Qi, Z. Wang, J. Huang, and Q. Xue, "Improving the quality of stripes in structured-light three-dimensional profile measurement," 2017.
[11] D. Naidu and R. B. Fisher, A comparison of algorithms for sub-pixel peak detection. University of Edinburgh, Department of Artificial Intelligence, 1991.
[12] Z. Y. Xu, H. Y. Zheng, and H. Y. Yang, "An improved Gaussian fitting method used in light-trap center acquiring," in Applied Mechanics and Materials, 2014, vol. 596, pp. 449-452: Trans Tech Publ.
[13] C. Rocchini, P. Cignoni, C. Montani, P. Pingi, and R. Scopigno, "A low cost 3D scanner based on structured light," in Computer Graphics Forum, 2001, vol. 20, no. 3, pp. 299-308: Wiley Online Library.
[14] X. Bai, "Morphological center operator for enhancing small target obtained by infrared imaging sensor," Optik-International Journal for Light and Electron Optics, vol. 125, no. 14, pp. 3697-3701, 2014.
[15] A. Landström, "Adaptive tensor-based morphological filtering and analysis of 3D profile data," Luleå tekniska universitet, 2012.
[16] Y. Li, J. Zhou, F. Huang, and L. Liu, "Sub-pixel extraction of laser stripe center using an improved gray-gravity method," Sensors, vol. 17, no. 4, p. 814, 2017.
[17] C. S. Fraser, "Digital camera self-calibration," ISPRS Journal of Photogrammetry and Remote sensing, vol. 52, no. 4, pp. 149-159, 1997.
[18] A. A. Al-Kharaz and A. K. Chong, "High accuracy smartphone video calibration for human foot surface mapping," in 2018 IEEE 3rd International Conference on Image, Vision and Computing (ICIVC), 2018, pp. 542-545: IEEE.
[19] E. E. Elnima, "A solution for exterior and relative orientation in photogrammetry, a genetic evolution approach," Journal of King Saud University-Engineering Sciences, vol. 27, no. 1, pp. 108-113, 2015.
[20] TRAN;, T. Anh;, and Vietnam, "Epipolar Resampling of Stereo Image Base on Airbase in the Digital," Land Governance and the Environment – Building the Capacity, 2009.
[21] M. F. Morgan, Epipolar resampling of linear array scanner scenes. University of Calgary, Department of Geomatics Engineering, 2004.
[22] W. Cho, T. Schenk, and M. Madani, "Resampling digital imagery to epipolar geometry," International Archives of Photogrammetry and Remote Sensing, vol. 29, pp. 404-404, 1993.
[23] T. Luhmann, S. Robson, S. Kyle, and J. Boehm, Close-range photogrammetry and 3D imaging. Walter de Gruyter, 2013.
[24] B. Kathariya, L. Li, Z. Li, J. Alvarez, and J. Chen, "Scalable point cloud geometry coding with binary tree embedded quadtree," in 2018 IEEE International Conference on Multimedia and Expo (ICME), 2018, pp. 1-6: IEEE.
[25] A. Nurunnabi, D. Belton, and G. West, "Diagnostic-robust statistical analysis for local surface fitting in 3D point cloud data," ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Science, Volumes I-3, pp. 269-274, 2012.
[26]   C. Wu, S. Agarwal, B. Curless, and S. M. Seitz, "Multicore bundle adjustment," in CVPR 2011, 2011, pp. 3057-3064: IEEE.
[27]   B. Triggs, P. F. McLauchlan, R. I. Hartley, and A. W. Fitzgibbon, "Bundle adjustment—a modern synthesis," in International workshop on vision algorithms, 1999, pp. 298-372: Springer.
Journal of Soft Computing and Information Technology
Volume 10, Issue 1 - Serial Number 31
Spring
April 2021
Pages 1-12

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