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  4. Vol 4, Issue 1, 2023

Calibration Method for Fisheye Camera Based on Multi-checkerboard Detection

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DOI: 10.23977/autml.2023.040104 | Downloads: 25 | Views: 497

Author(s)

Zhou Su 1,2, Zhu Xiaofeng 1, Lu Yanda 1

Affiliation(s)

1 School of Automotive Studies, Tongji University, Shanghai, China
2 Sino-German College, Tongji University, Shanghai, China

Corresponding Author

Zhu Xiaofeng

ABSTRACT

This paper proposes a fisheye camera calibration method based on multiple chessboard detection. To address the complexity and multiple-frame requirement of traditional calibration methods, this method detects multiple chessboard corner points using libcbdetect algorithm and obtains pixel coordinates. Then, it uses a depth-first search algorithm to obtain the world coordinates of the chessboard corners and calculates the homography matrix based on the world-pixel coordinates pair through RANSAC algorithm. Finally, the undistorted image is transformed into a bird's eye view (BEV) using the obtained homography matrix. This method is simple and effective, and can improve the accuracy of lane keeping functions, which is of practical significance in autonomous driving applications.

KEYWORDS

Fisheye camera, Calibration, Inverse perspective transformation, Corner detection

CITE THIS PAPER

Zhou Su, Zhu Xiaofeng, Lu Yanda, Calibration Method for Fisheye Camera Based on Multi-checkerboard Detection. Automation and Machine Learning (2023) Vol. 4: 24-31. DOI: http://dx.doi.org/10.23977/autml.2023.040104.

REFERENCES

[1] Li H., Yang M. (2008). Camera Distortion Parameter Calibration Based on Nonlinear Inverse Perspective Transformation. Journal of Shanghai Jiaotong University, (10), 1736-1739.
[2] Ha JE. Automatic detection of chessboard and its applications [J]. Optical Engineering, 2009, 48(6):067205-067205-8.
[3] Kannal J, Brandt S S. A generic camera model and calibration method for conventional, wide-angle, and fish-eye lenses [J]. IEEE Transactions on Pattern Analysis and Machine Intelligence-PAMI, 2006, 28(8):1335-1340.
[4] Scaramuzza Davide, Agostino Martinelli, and Roland Siegwart. "A flexible technique for accurate omnidirectional camera calibration and structure from motion." Fourth IEEE International Conference on Computer Vision Systems (ICVS'06). IEEE, 2006.
[5] Harris Chris, and Mike Stephens. "A combined corner and edge detector." Alvey vision conference. Vol. 15. No. 50. 1988.
[6] Shi Jianbo. "Good features to track." 1994 Proceedings of IEEE conference on computer vision and pattern recognition. IEEE, 1994.
[7] Geiger Andreas, et al. "Automatic camera and range sensor calibration using a single shot." 2012 IEEE international conference on robotics and automation. IEEE, 2012.
[8] Devernay Frédéric. A non-maxima suppression method for edge detection with sub-pixel accuracy. Diss. INRIA, 1995.
[9] Vincent O. Rebecca, and Olusegun Folorunso. "A descriptive algorithm for sobel image edge detection." Proceedings of informing science & IT education conference (InSITE). Vol. 40. 2009.
[10] Carreira-Perpinan, Miguel A. "Gaussian mean-shift is an EM algorithm." IEEE Transactions on Pattern Analysis and Machine Intelligence 29.5 (2007): 767-776.
[11] Tarjan Robert. "Depth-first search and linear graph algorithms." SIAM journal on computing 1.2 (1972): 146-160.
[12] Derpanis Konstantinos G. "Overview of the RANSAC Algorithm." Image Rochester NY 4.1 (2010): 2-3.
[13] Liu Yu, et al. "Automatic chessboard corner detection method." IET Image Processing 10.1 (2016): 16-23.

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