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Automatic chessboard corner detection method

机译：棋盘角自动检测方法

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Chessboard corner detection is a necessary procedure of the popular chessboard pattern-based camera calibration technique, in which the inner corners on a two-dimensional chessboard are employed as calibration markers. In this study, an automatic chessboard corner detection algorithm is presented for camera calibration. In authors’ method, an initial corner set is first obtained with an improved Hessian corner detector. Then, a novel strategy that utilises both intensity and geometry characteristics of the chessboard pattern is presented to eliminate fake corners from the initial corner set. After that, a simple yet effective approach is adopted to sort the detected corners into a meaningful order. Finally, the sub-pixel location of each corner is calculated. The proposed algorithm only requires a user input of the chessboard size, while all the other parameters can be adaptively calculated with a statistical approach. The experimental results demonstrate that the proposed method has advantages over the popular OpenCV chessboard corner detection method in terms of detection accuracy and computational efficiency. Furthermore, the effectiveness of the proposed method used for camera calibration is also verified in authors’ experiments.
机译：棋盘角检测是流行的基于棋盘图案的相机校准技术的必要步骤，其中将二维棋盘上的内角用作校准标记。在这项研究中，提出了一种用于相机校准的自动棋盘角检测算法。在作者的方法中，首先使用改进的Hessian拐角检测器获得初始拐角集。然后，提出了一种利用棋盘图案强度和几何特征的新颖策略，可以从初始角点集中消除假角点。之后，采用一种简单而有效的方法将检测到的角点分类为有意义的顺序。最后，计算每个角的子像素位置。所提出的算法仅需要用户输入棋盘大小，而所有其他参数都可以通过统计方法自适应地计算。实验结果表明，该方法在检测精度和计算效率上均优于流行的OpenCV棋盘角检测方法。此外，作者的实验也验证了所提出的用于相机校准的方法的有效性。

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