Research on Verification Method of OpenGL Simulated Image Based on Camera Calibration

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Abstract:

OpenGL can correctly simulate real photogrammetric imaging by setting reasonable parameters. It’s an important tool to achieve the simulation of real three-dimensional object or scene imaging to two-dimensional CCD (Charge-coupled Device) plane. However, the images are lack of reliability verify. To solve this problem, we propose a method that can verify OpenGL simulated images on the basis of analyzing OpenGL image-forming principle. Firstly, the checkerboard images of different positions are taken by real camera and intrinsic and external parameters are calibrated. Subsequently, we use OpenGL to produce the same intrinsic and external parameters of checkerboard image by setting correct parameters. Finally, the simulated and real images’ matching point pair RMSE value is calculated based on Harris operator. By comparison, the validity and reliability of OpenGL simulated images are verified by some numerical simulation.

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3859-3862

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August 2014

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© 2014 Trans Tech Publications Ltd. All Rights Reserved

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[1] Reiners Dir.Climbing Longs Peak: The Steep Road to the Future of OpenGL[J].Computer Graphics and Applications.IEEE, 2007, 27(4): 84—89.

DOI: 10.1109/mcg.2007.79

Google Scholar

[2] Adler D, Murdoch D. rgl: 3D visualization device system (OpenGL)[J]. R package version 0. 92, 2012, 798.

Google Scholar

[3] Han Yi, Sun Hua-yan, Li Ying-chun, etc. Method of Space Object Imaging Simulation Based on OpenGL[J]. Computer Simulation, 2010, 27(6): 267-270, 289.

Google Scholar

[4] Niu Ruo-xi, Yang xin. Visual Simulation of Satellite Motion in Orbit[J]. Computer Simulation, 2013, 30(8): 50-53.

Google Scholar

[5] Wang Yan-bo. The research and application of multi planar reconstruction based on OpenGL in visual medical image system[D]. Zhejiang University of Technology, (2012).

Google Scholar

[6] Yan long, Hua zhen, Chen Cheng-jun, etc. Research on Simulation and Verification Technologies of Photogrammetry System[J]. Journal of System Simulation, 2013, 25(6): 1231-1234, 1240.

Google Scholar

[7] Ding Nan-Nan, Liu Yan-ying, Zhang ye, etc. Fast image registration based on SURF-DAISY algorithm and random kd trees[J]. Optoelectronics. Laser, 2012, 07: 1395-1402.

Google Scholar

[8] Yan Hui, Jiang Peng, Chen Bei. Digital Image Processing Technique based on MATLAB Toolbox[J]. Microcomputer Information, 2010, 26: 214-216.

Google Scholar

[9] Fan Zhi-hua, Wang Chun-peng, Rao Chang-hun, etc. High accuracy subpixel image registration based on phase-only correlation of Harris strength[J]. Application Research of Computers, 2011, 02: 788-791.

Google Scholar

[10] Yao Yao, Hu Zhong-xiang, Shi Xiao-jun, etc. Camera self-calibration on a sub-pixel level to apply extract corners by Harris algorithm[J]. Electronic Design Engineering, 2009, 05: 61-62+65.

Google Scholar