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An automatic camera calibration method based on checkerboard

机译:基于自动相机标定方法棋盘

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摘要

The traditional camera calibration methods faces many problems, such as the need for manual operation and high-quality images as well as the heavy time consumption. To solve these problems, this paper puts forward an adaptive extraction and matching algorithm for checkerboard inner-corners for camera calibration. Firstly, the coordinates of all corner points of the checkerboard were derived by the Harris algorithm. Then, the four vertices of the checkerboard were acquired in the image coordinate system based on polygonal convexity. After that, the coordinates of the inner-corner points of the checkerboard image were obtained against the judgement rules that distinguish inner-corner points from other points on that image. On this basis, the matching relationship was established between the inner-corner points of the checkerboard image in the image coordinate system and those in the checkerboard coordinate system. Finally, the theoretical modelling, judgement rules and a mature camera calibration model were integrated for automatic camera calibration experiments. The results show that the automatic camera calibration method based on the proposed algorithm consumed 75% less time than the Matlab toolbox and controlled the error within ±0.3 pixels. This research provides a real-time, robust and accurate automatic camera calibration method for engineering applications.
机译:传统的摄像机标定方法许多问题,如需要手册以及操作和高质量的图像沉重的时间消耗。提出了一种自适应提取并为棋盘匹配算法其它地方的相机标定。所有角点的坐标棋盘被哈里斯派生算法。棋盘图像中获得的基于多边形凸性的坐标系统。在那之后,内角的坐标点的棋盘图像区分的判断规则内角点与其他点的形象。内角点之间建立了棋盘的图像在图像坐标系统和棋盘坐标系统。判断规则和一个成熟的相机标定模型集成自动相机标定实验。基于自动相机标定方法该算法消耗减少75%比Matlab工具箱和误差控制在±0.3像素。实时的、健壮的和准确的自动相机标定方法的工程应用。

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