21. Adaptive adjustment of brightness and blur of the camera for high precision internal parameter calibration.
- Author
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Ding, Weili, Tan, Weimin, Liu, Guoqing, Zhang, Heng, and Wang, Wenfeng
- Subjects
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CAMERA calibration , *CALIBRATION , *COMPUTER vision , *CIRCLE , *CAMERAS , *PROBLEM solving - Abstract
• Proposed an adaptive exposure adjustment algorithm, eliminating the need for manual intervention during the calibration process, making the calibration process more robust to environmental changes. • Proposed an adaptive blur adjustment algorithm, enhancing the clarity of calibration images, addressing the issue of uncontrollable blurring in previous algorithms, and improving the accuracy of camera intrinsic parameter calibration. • Designed a semi-automatic high-precision calibration strategy that addresses significant discrepancies in calibration results obtained from different calibration processes in traditional algorithms, thus improving robustness. Camera calibration is a prerequisite for many computer vision tasks, such as visual measurement and visual localization. This paper proposes a new method for high-precision calibration of camera intrinsic parameters. By dynamically adjusting image brightness and blur to cope with changes in external lighting conditions and camera working distance, high-precision internal parameter measurement is achieved. This method solves the problems of the traditional camera intrinsic parameter calibration process being cumbersome and susceptible to changes in the placement of calibration boards and fluctuations in external lighting conditions. Firstly, an adaptive exposure adjustment algorithm is proposed to adjust the camera exposure value by statistically analyzing the average gray value of randomly selected rectangular regions on the calibration board, thereby solving the problem of the camera calibration accuracy being affected by overly bright or dark environments. Subsequently, an evaluation criterion and adaptive adjustment strategy for adjusting image blur are proposed. By extracting edge points of feature circles and obtaining the slope of the fitted curve, the relationship between edge sharpness and slope is utilized to adjust the image blur. Finally, the proposed method achieves high-precision semi-automatic calibration. Experimental results demonstrate that the proposed method has significant advantages in terms of correctness, robustness, and flexibility, with an average reprojection error of 0.0167. [ABSTRACT FROM AUTHOR]
- Published
- 2024
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