Acta Optica Sinica, Volume. 42, Issue 8, 0815001(2022)
Checkerboard Corners Sub-Pixel Refinement Based on Edge Direction Projection
With the popularization of visual measurement technology in engineering, more and more visual calibration and measurement need to be carried out by non-professionals in the workshop site, which will cause checkerboard images to contain more noise. In order to achieve robust and accurate sub-pixel refinement of checkerboard corner under noise, a checkerboard corners sub-pixel refinement method based on edge direction projection is proposed. First, the initial edge direction is calculated based on the non-maximum suppression algorithm. Then, the edge direction is refined based on the least weighted square fitting method. Finally, the sub-pixel coordinates of the checkerboard corners are refined based on the maximum projection of the edge direction. The results show that in the high-quality checkerboard images, the maximum measurement errors of checkerboard edge length are all less than 0.021 mm, and the average measurement errors of checkerboard edge length are all less than 0.006 mm. In the checkerboard image with Gaussian noise and corner pollution, the maximum deviation of checkerboard edge length measurement of the proposed method is less than 0.05 mm, and the average deviation of checkerboard edge length measurement is less than 0.02 mm.
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Shengfeng Chen, Bing Chen, Jian Liu. Checkerboard Corners Sub-Pixel Refinement Based on Edge Direction Projection[J]. Acta Optica Sinica, 2022, 42(8): 0815001
Category: Machine Vision
Received: Sep. 26, 2021
Accepted: Nov. 8, 2021
Published Online: Mar. 30, 2022
The Author Email: Chen Shengfeng (shengfengc@hnu.edu.cn), Liu Jian (liujian@hnu.edu.cn)