Abstract Obtaining an optimal tradeoff between accuracy and efficiency in ellipse detection is a significant challenge. In this paper, we propose a fast, high-precision ellipse detection method that utilizes arc selection and grouping strategies to significantly reduce the computation amount. A fast corner detection algorithm is also proposed. In the proposed method, to generate ellipse candidates comprehensively, both grouped and ungrouped-salient arcs are fitted. Further, the salient ellipse candidates are selected as final detections that are subject to the selection strategy, which realizes both validation and de-redundancy (clustering) functions. A complexity analysis of the method revealed that the detection time is linearly related to the number of edge points. The results of extensive experiments conducted on three public datasets demonstrate that the proposed method is approximately 75% faster than state-of-the-art methods with comparable or higher precision, and its detection time is less than 30 ms in most cases.

中文翻译：

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快速高精度椭圆检测方法

摘要 在椭圆检测中获得准确度和效率之间的最佳折衷是一项重大挑战。在本文中，我们提出了一种快速、高精度的椭圆检测方法，该方法利用弧选择和分组策略来显着减少计算量。还提出了一种快速角点检测算法。在所提出的方法中，为了综合生成椭圆候选，分组和未分组的显着弧都被拟合。此外，选择显着椭圆候选作为最终检测，受选择策略的约束，这实现了验证和去冗余（聚类）功能。该方法的复杂性分析表明，检测时间与边缘点的数量线性相关。