15 May 2018 Automatic checkerboard detection for camera calibration using self-correlation
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Abstract
The checkerboard is a frequently used pattern in camera calibration, an essential process to get intrinsic parameters for more accurate information from images. An automatic checkerboard detection method that can detect multiple checkerboards in a single image is proposed. It contains a corner extraction approach using self-correlation and a structure recovery solution using constraints related to adjacent corners and checkerboard block edges. The method utilizes the central symmetric feature of the checkerboard crossings as well as the spatial relationship of neighboring checkerboard corners and the grayscale distribution of their neighboring pixels. Five public datasets are used in the experiments to evaluate the method. Results show high detection rates and a short average runtime of the proposed method. In addition, the camera calibration accuracy also presents the effectiveness of the proposed detection method with reprojected pixel errors smaller than 0.5 pixels.
© 2018 SPIE and IS&T
Yizhen Yan, Peng Yang, Lei Yan, Jie Wan, Yanbiao Sun, Kevin Tansey, Anand K. Asundi, Hongying Zhao, "Automatic checkerboard detection for camera calibration using self-correlation," Journal of Electronic Imaging 27(3), 033014 (15 May 2018). https://doi.org/10.1117/1.JEI.27.3.033014 Submission: Received 11 December 2017; Accepted 20 April 2018
Submission: Received 11 December 2017; Accepted 20 April 2018
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