首页> 外文会议>Intelligent Robots and Systems, 1999. IROS '99. Proceedings. 1999 IEEE/RSJ International Conference on >Ellipse fitting and parameter assessment of circular object targets for robot vision
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Ellipse fitting and parameter assessment of circular object targets for robot vision

机译:用于机器人视觉的圆形目标的椭圆拟合和参数评估

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The least squares fitting minimizes the squares sum of error-of-fit in predefined measures. By the geometric fitting, the error distances are defined with the shortest distances from the given points to the geometric feature to be fitted. For the geometric fitting of ellipse, a robust algorithm is proposed. This is based on the coordinate description of the corresponding point on the ellipse for the given point, where the connecting line of the two points is the shortest path from the given point to the ellipse. As a practical application example, we show the geometric ellipse fitting to the image of circular point targets, where the contour points are weighted with their image gradient across the boundary of the image ellipse.
机译:最小二乘拟合使预定义度量中的拟合误差的平方和最小。通过几何拟合,误差距离定义为从给定点到要拟合的几何特征的最短距离。针对椭圆的几何拟合,提出了一种鲁棒算法。这基于给定点在椭圆上对应点的坐标描述,其中两个点的连接线是从给定点到椭圆的最短路径。作为一个实际的应用示例,我们显示了适合圆点目标图像的几何椭圆,其中轮廓点通过其在图像椭圆边界上​​的图像梯度进行加权。

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