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http://dx.doi.org/10.9709/JKSS.2010.19.1.023

Image Data Loss Minimized Geometric Correction for Asymmetric Distortion Fish-eye Lens  

Cho, Young-Ju (이화여자대학교 컴퓨터정보통신공학과)
Kim, Sung-Hee (이화여자대학교 컴퓨터정보통신공학과)
Park, Ji-Young (이화여자대학교 컴퓨터정보통신공학과)
Son, Jin-Woo (현대.기아자동차 연구개발 총괄본부 ASV 개발팀)
Lee, Joong-Ryoul (현대.기아자동차 연구개발 총괄본부 ASV 개발팀)
Kim, Myoung-Hee (이화여자대학교 컴퓨터정보통신공학과)
Publication Information
Journal of the Korea Society for Simulation / v.19, no.1, 2010 , pp. 23-31 More about this Journal
Abstract
Due to the fact that fisheye lens can provide super wide angles with the minimum number of cameras, field-of-view over 180 degrees, many vehicles are attempting to mount the camera system. Not only use the camera as a viewing system, but also as a camera sensor, camera calibration should be preceded, and geometrical correction on the radial distortion is needed to provide the images for the driver's assistance. In this thesis, we introduce a geometric correction technique to minimize the loss of the image data from a vehicle fish-eye lens having a field of view over $180^{\circ}$, and a asymmetric distortion. Geometric correction is a process in which a camera model with a distortion model is established, and then a corrected view is generated after camera parameters are calculated through a calibration process. First, the FOV model to imitate a asymmetric distortion configuration is used as the distortion model. Then, we need to unify the axis ratio because a horizontal view of the vehicle fish-eye lens is asymmetrically wide for the driver, and estimate the parameters by applying a non-linear optimization algorithm. Finally, we create a corrected view by a backward mapping, and provide a function to optimize the ratio for the horizontal and vertical axes. This minimizes image data loss and improves the visual perception when the input image is undistorted through a perspective projection.
Keywords
Vehicle fish-eye lens; Asymmetric distortion; Geometric correction;
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1 R. Swaminathan and S.K. Nayar, "Non-metric calibration of wide-angle lenses and polycameras," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 22, pp. 1172-1178, 2000.   DOI   ScienceOn
2 Z. Zhang, "A flexible new technique for camera calibration," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 22, pp. 1330-1334, 2000.   DOI   ScienceOn
3 M.A. Abidi and R.O. Eason, "Camera calibration in robot vision," Proc, 4th Scandinavian Conference on Image Analysis, pp. 471-478, 1985.
4 S. Shah and J.K. Aggarwal, "Intrinsic parameter calibration procedure for a (high distortion) fish-eye lens camera with distortion model and accuracy estimation," Pattern Recognition, vol. 29, pp. 1775-1788, 1996.   DOI   ScienceOn
5 R.Y. Tsai, "A versatile camera calibration technique for high accuracy 3D machine vision metrology using off-theshelf TV cameras and lenses," IEEE Journal of Robotics Autom, vol. RA-3, pp. 323-344, 1986.
6 D. Scaramuzza and A. Martinelli, "A flexible technique for accurate omnidirectional camera calibration and structure from motion," IEEE International Conference on Computer Vision Systems, 2006.
7 신주홍, 남동환, 권기준, 정순기, "Ellipsoid를 이용한 어안렌즈의 Non-metric 접근 왜곡 보정 기법," HCI 2005, vol. 14, pp.83-89, 2005.
8 C. Mei and P. Rives, "Single view point omnidirectional camera calibration from planar grids," Proc. IEEE International Conference on Robotics and Automation, pp. 3945-3950, 2007.
9 D.C. Brown, "Close range camera calibration," Photogrammetric Engineering and Remote sensing, vol. 37, pp. 885-566, 1971.
10 S.B. Kang, "Semi-automatic methods for recovering radial distortion parameters from a single image," Technical Reports Series CRL 97/3, pp. 21, 1997.
11 B. Micusik, T. Pajdla, "Autocalibration and 3D reconstruction with non-central catadioptric cameras," IEEE Internation Conference on Computer Vision and Pattern Recognition, 2004.
12 Besma Roui-Abidi and Chris Broaddus and Vitaliy Orekhov and Mongi Abidi, "A Generalized Full Scale Camera Calibration Method with Optimized Complexity," Proc. Fourth IEEE International Conference Multi-Conference on Systems, 2007.
13 Philip E. Gill and Walter Murray, "Algorithms for the solution of the nonlinear least-squares problem," SIAM Journal on Numerical Analysis, vol. 15, pp. 977-992, 1978.   DOI   ScienceOn
14 R. Unnikrishnan and M. Hebert, Fast extrinsic of a laser rangefinder to a camera, Technical Report Robotics Institute, Carnegie Mellon University, 2005.
15 F. Devernay and O. Faugeras, "Straight lines have to be straight," Machine Vision and Applications, vol. 13, pp. 14-24, 2001.   DOI   ScienceOn
16 S.S. Beauchemin, R. Bajcsy and G. Givaty, "A unified procedure for calibrating intrinsic parameters of fish-eye lenses," Proc, of the Conference on Vision Interface, pp. 272-279, 1999.
17 J. Heikkila, "Geometric camera calibration using circular control points," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 22, pp. 1066-1077, 2000.   DOI   ScienceOn
18 J. P. Barreto and K. Aniilidis, "Fundamental matrix for cameras with radial distortion," International Conference On Computer Vision, pp. 625-632, 2005.
19 H. Longuet-Higgins, "Acomputer algorithm for reconstructing a scene from two projections," Nature, vol. 293, pp. 133-135, 1981.   DOI
20 Y. Xiong and K. Turkowski, "Creating image-based VR using a self-calibrating fisheye lens," Proc, of the Conference on Computer Vision and Pattern Recognition, pp. 237-243, 1997.
21 H. Bakstein and T. Pajdla, "Panoramic mosaicing with a $183^\circ$ field of view lens," Proc, of the IEEE Workshop on Omnidirectional Vision, pp. 60-67, 2002.
22 C. Brauer-Burchardt and K. Voss, "A new algorithm to correct fish-eye- and strong wide-angle-lens-distortion from single images," Proc, of the Conference on Image Processing, pp. 225-228, 2001.