A fast and precise method for ellipse detection is proposed in this paper. The method aims at clearly removing the lines and curves which are not ellipse edges to improve the ellipse fitting. In arc extraction, the arcs are divided into four categories according to the gradient, and the size constraint is exploited to remove the interference lines. Then, the arc relative position constraints and the tangent lines constraint are employed to exactly group the arcs that belong to the same ellipse into a set. Finally, a post-processing approach is developed to remove the invalid ellipses. Due to the effective removal of the interference edges and the designed geometric multi-constraint, the computational costs of arc grouping and parameter estimation are dramatically reduced, and the fitting results are finely agreeable to the actual ellipse contours. The performance is evaluated with 3600 synthetic images and 1517 real images, and the experimental results demonstrate that the proposed method runs much faster than the current speed leading methods with the comparable or higher F-measure.

中文翻译：

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通过边缘筛选和聚合的实时精确椭圆检测器

提出了一种快速，精确的椭圆检测方法。该方法旨在清楚地去除不是椭圆边缘的线和曲线，以改善椭圆拟合。在电弧提取中，根据梯度将电弧分为四类，并利用尺寸约束去除干扰线。然后，使用圆弧相对位置约束和切线约束将属于相同椭圆的圆弧精确分组为一组。最后，开发了一种后处理方法来删除无效的椭圆。由于有效地消除了干涉边缘和设计的几何多约束，因此大大降低了电弧分组和参数估计的计算成本，并且拟合结果与实际的椭圆轮廓非常吻合。F-措施。