Distortion Correction for the Gun Barrel Bore Panoramic Image

Abstract:

Single Reflector Panoramic Imaging System (SRPIS) has been widely used because of its advantages such as simple structure, fast imaging, integration and miniaturization. It can observe objects around the reflector mirror, which fits for the quality inspection of gun barrel bore. However, its images often suffer from serious distortions in radial and tangential directions. Therefore, to ensure the accuracy of captured images, distortion must be eliminated. In this paper, a distortion correction method is proposed based on the imaging characteristics of SRPIS. Firstly the relationship between the height of a certain point on the gun barrel bore and the radius of image point is derived. Then the correction model is built based on the relationship. Aiming at the captured annular image, a new chessboard corner detection algorithm is proposed. The correction parameters are obtained by using the algorithm according to the labeled image. The real experiment results demonstrate that the correction effects of radial and tangential distortions are satisfactory. The error is controlled at sub-pixel level.

• Periodical: Applied Mechanics and Materials (Volumes 427-429)
• Pages: 680-685
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.427-429.680
• Online since: September 2013
• Authors: Fu Qiang Peng*, Qiang Chen, Jun Wei Bao
• Keywords: Chessboard Corner Detection, Distortion Correction, Projection Relationship, Single Reflector Panoramic Imaging System

References

[1] LI Y, ZHENG H, LUAN J, et al. Present Status and Prospects of Flaw Detection for Gun Barrel Bore [J]. Journal of Ordnance Engineering College, 2009, 1: 013.

[2] Liefeng Z, Huajun F, Qi L, et al. Optical Inspection System for the Inner Surface of a Pipe[C]/Electronic Measurement and Instruments, 2007. ICEMI'07. 8th International Conference on. IEEE, 2007: 1-584-1-587.

DOI: 10.1109/icemi.2007.4350517

[3] Islam M R, Naser M A, Hasan M R, et al. Using catadioptric sensor to obtain image of the inner surface of a pipe and detection and analysis of faults by image processing[C]/Computer and Information Technology (ICCIT), 2011 14th International Conference on. IEEE, 2011: 607-610.

DOI: 10.1109/iccitechn.2011.6164860

[4] Xiao X, YANG G. A present and development of panoramic imaging technique[J]. Optical Instruments, 2007, 4: 017.

[5] Powell I. Panoramic lens: U.S. Patent 5, 473, 474[P]. 1995-12-5.

[6] Lei J, Fu J, Guo Q. Distortion correction on gun bore panoramic image[C]/Quality, Reliability, Risk, Maintenance, and Safety Engineering (ICQR2MSE), 2011 International Conference on. IEEE, 2011: 956-959.

DOI: 10.1109/icqr2mse.2011.5976762

[7] Lee S H, Lee S K, Choi J S. Correction of radial distortion using a planar checkerboard pattern and its image[J]. Consumer Electronics, IEEE Transactions on, 2009, 55(1): 27-33.

DOI: 10.1109/tce.2009.4814410

[8] Jiyong Zeng. Catadioptric omnidirectional stereo imaging[D]. Sichuan Univercity, (2003).

[9] Xiao Xiao, Wei Wang, Kai Bi. Panoramic annular lens distortion correction using the cylinder perspective projection model[J]. Journal of Xidian University(1): 87-92.

[10] Miranda-Luna R, Daul C, Blondel W C P M, et al. Mosaicing of bladder endoscopic image sequences: Distortion calibration and registration algorithm[J]. Biomedical Engineering, IEEE Transactions on, 2008, 55(2): 541-553.

DOI: 10.1109/tbme.2007.903520

[11] LIU J, LIU S. Optimization choice for parameters of photoelectric spying bore optical system [J]. Opto-electronic Engineering, 2002, 3: 012.

[12] Baker S, Nayar S K. A theory of single-viewpoint catadioptric image formation[J]. International Journal of Computer Vision, 1999, 35(2): 175-196.

[13] Barreto J P, Araujo H. Geometric properties of central catadioptric line images and their application in calibration[J]. Pattern Analysis and Machine Intelligence, IEEE Transactions on, 2005, 27(8): 1327-1333.

DOI: 10.1109/tpami.2005.163

[14] Weixing Z, Changhua M, Libing X, et al. A fast and accurate algorithm for chessboard corner detection[C]/Image and Signal Processing, 2009. CISP'09. 2nd International Congress on. IEEE, 2009: 1-5.

DOI: 10.1109/cisp.2009.5304332

[15] Hu H, Xiong Y. A New Algorithm for Chessboard Grid Corners Detection Based on Two Successive Radon Transform [J]. Acta Scientiarum Naturalium Universitatis Sunyatseni, 2003, 2: 007.

[16] De la Escalera A, Armingol J M. Automatic chessboard detection for intrinsic and extrinsic camera parameter calibration[J]. Sensors, 2010, 10(3): 2027-(2044).

DOI: 10.3390/s100302027

[17] Hu X, Du P, Zhou Y. Automatic corner detection of chess board for medical endoscopy camera calibration[C]/Proceedings of the 10th International Conference on Virtual Reality Continuum and Its Applications in Industry. ACM, 2011: 431-434.

DOI: 10.1145/2087756.2087837

[18] Xingfang Y, Yumei H, Feng G. A simple camera calibration method based on sub-pixel corner extraction of the chessboard image[C]/Intelligent Computing and Intelligent Systems (ICIS), 2010 IEEE International Conference on. IEEE, 2010, 3: 688-692.

DOI: 10.1109/icicisys.2010.5658280

[19] Bradski G, Kaehler A. Learning OpenCV: Computer vision with the OpenCV library[M]. O'Reilly Media, Incorporated, 2008, 407-438.

[20] ZHAO L, FENG H, BAI J, et al. Image restoration for super hemisphere annular imaging system[J]. Journal of Zhejiang University (Engineering Science), 2009, 11: 025.