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Fringe Projection Profilometry System Calibration and Multiview Range Image Registration
|關鍵字:||Phase shifting;相位移;Gray code;Gamma correction;Registration;格雷式編碼;伽瑪曲線調整;形貌註冊||出版社:||機械工程學系所||引用:||1.李勇民，條紋投射法於微型曲面量測之研究，國立中興大學機械工程研究所碩士學位論文，台中，2004。 2.李建緯，格雷氏編碼與相位移在三維曲面量測之應用，國立中興大學機械工程研究所碩士學位論文，台中，2004。 3. 高玉和，微型元件多視角三維形貌疊合之研究，國立中興大學機械工程研究所碩士學位論文，台中，2005。 4.P. J. Besl and N. D. McKay, "A method for registration of 3-D shapes," IEEE Transactions on Pattern Analysis and Machine Intelligence, pp. 239–256, 1992. 5.G. Sansoni, S. Corini, S. Lazzari, R. Rodella, and F. Docchio, " Three-dimensional imaging based on Gray-code light projection: characterization of the measuring algorithm and development of a measuring system for industrial applications," Applied Optics, Vol. 36, No. 19, pp. 4463-4472, 1997. 6.G. Sansoni, M. Carocci, and R. Rodella, "Three-dimensional vision based on a combination of gray-code and phase-shift light projection: analysis and compensation of the systematic errors, " Applied Optics, Vol. 38, No. 31, pp. 6565-6573, 1999. 7.C. Quan, C. J. Tay, X. Y. He, X. Kang, and H. M. Shang, "Microscopic surface contouring by fringe projection method," Optics and Laser Technology, Vol. 34, pp. 547-552, 2002. 8.M. Chang and K. H. Lin, "Non-contact scanning measurement utilizing a space mapping method," Opt. Laser Eng., No. 30, pp. 503-512, 1999. 9.A. Goshtasby, " Three-dimensional model construction from multiview range images: survey with new results," Pattern Recog. Vol. 31, No. 11, pp. 1705-1714, 1998. 10.Y. Chen and G. Medioni, "Object Modelling by Registration of Multiple Range Images," Image and Vision Computing, Vol. 10, No. 3, pp. 145-155, 1992. 11.J. P. Thirion, "Extremal points: definition and application to 3D image registration," CVPR94, pp. 587-592, 1994. 12.A. E. Johnson and S. B. Kang ,"Registration and Integration of Textured 3D Data," Proc.Int''l Conf. on Recent Advances in 3D Digital Imaging and Modeling, IEEE Computer Society Press, Los Alamitos, Calif., pp. 234-241, 1997. 13.T. Jost, "fast geometric matching for shape registration," PhD thesis, University of Neuchâtel, 2002. 14. C. Schütz, "Geometric Point Matching of free-form 3D objects," PhD thesis,Université de Neuchâtel, 1998. 15.C. Dorai, G. Wang, A. K. Jain, and C. Mercer," Registration and integration of multiple object views for 3D model construction," IEEE Trans. Pat. Anal. and Mach. Intel., Vol. 20, No. 1, pp. 83-89, 1998. 16.G. Turk and M. Levoy, "Zippered Polygon Meshes from Range Images," Proc. ACM SIGGRAPH 94, pp. 311-318, 1994. 17.Yonghuai Liu, Baogang Wei, "Developing structural constraints for accurate registration of overlapping range images, "Robotics and Autonomous System, Vol. 47,pp.11-30,2004. 18.J. H. Friedman, J. L. Bentley, and R. A. Finkel, " An Algorithm for Finding Best Matches in Logarithmic Expected Time," ACM Trans. Math. Softw, Vol. 3, No. 3, pp. 209-226, 1977. 19.Z. Zhang, "Iterative point matching for registration of free-form curves and surfaces," International Journal of Computer Vision, Vol. 13, pp.119-152, 1994. 20.T. Jost, and H. Hügli, "Fast ICP Algorithms for Shape Registration," DAGM-Symposium, pp. 91-99, 2002. 21.D. Chetverikov , D. Svirko , D. Stepanov and P. Krsek , "The Trimmed Iterative Closest Point Algorithm," Proc. IEEE Int''l Conf. Pattern Recognition, pp.545-548, 2002. 22.D. Chetverikov, D. Stepanov, and P. Krsek, "Robust Euclidean alignment of 3D point sets: the trimmed iterative closest point algorithm," Image Vision Comput, Vol. 23, No. 3, pp. 299-309, 2005. 23.N. Li, "Accurate integration of surface profile data with quantitative error analysis," Experimental Mechanics, Vol. 41, No. 1, pp. 77-83, 2001. 24.D. Akca, " A New Algorithm for 3D Surface Matching," Int. Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences(ISPRS) , pp. 960-965, 2004. 25.A. J. Stoddart, and A. Hilton, "Registration of multiple point sets," Proc. 13th Int. Conf. on Pat. Recog., Vol II, pp. 40-44, 1996. 26.John Williams ,Mohammed Bennamoun , "Simultaneous Registration of Multiple Corresponding Point Set," Computer vision and Image Understanding, Vol. 81, pp.117-142, 2001. 27. R. Y. Tsai, "A Versatile Camera Calibration Technique for High-Accuracy 3D Machine Vision Metrology using of-the-shelf TV cameras and Lenses," IEEE. J. of Robotics and Automation,RA-3(4),pp.323-344,1987. 28. Zhengyou Zhang, "A flexible New Technique for Camera Calibration," IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 22, pp.1330-1333 , 2000. 29.J. Moré, B. Garbow and K. Hillstrom,"MINPACK," Argonne National Laboratory, http://www.netlib.org/minpack. 30. Open Source Computer Vision Library , OpenCV, http://sourceforge.net/projects/opencvlibrary.||摘要:||
The CMM is used for surface profilometry traditionally, but it is not only expensive but also time consuming. With the computer technique promotes, the measurement uses the computer vision became convenient and inexpensive. The purpose of this paper is to establish a three-dimensional contours rebuilding system, which is economical and simple.
This paper describes the usage the liquid crystal display (LCD) which projects the fringe projection onto the object's surface. Then the triangulation principle is used to get the surface profile. For improving the accuracy of the system, we have to modify the system error, which results from lens distortion and the nonlinearity of the VGA display card, LCD projector and image grab. Generally speaking, there is always a Gamma correction for display equipment to accommodate the human's visual system, LCD for example. This correction makes brightness nonlinear problem and influences the phase accuracy, so we need calibration to improve the brightness nonlinear problem.
The measurement system obtains the single view profile information by means of the Gray-code method and phase-shifting technique to calculate the absolute phase, and the mapping relationship between the measured points and image pixel. Then we execute the range image registration and shortest path algorithm for all views. According to the shortest path and the transformation of each view, we can acquire the initial model. Finally, we execute the simultaneous regulating produce to obtain the whole contours of component.
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