结合多阶段优化的圆检测算法

在常规圆检测算法中，Hough变换、随机Hough变换以及随机圆检测算法的检测效率低，导致难以适用于复杂场景或者对检测速度有较高要求的情况。为了提高圆检测的效率，本文从采样点的选取、候选圆的确定以及真圆的确认3个阶段进行分析，结合这3个阶段的优化方法，提出一种结合多阶段优化的圆检测算法。人工图像和实际图像的实验结果表明：该算法较其他算法有效地提高了圆检测的速度，并且具有较好的检测鲁棒性和检测精度。

Multi-stage Optimized Algorithm for Circle Detection

As a basic and fundamental issue in computer vision area, many algorithms have been proposed to address the issue of circle detection, such as Hough transform, randomized Hough transform, randomized circle detection and so on. However, the low efficiency of these methods makes them hard to be used in complicated situations or conditions that require much higher circle detection speed. To improve the efficiency of circle detection, this paper analyzes three stages, including the selection of sampling points, the determination of candidate circle and the confirmation of true circle. Combined with the optimization of these three stages, a circle detection algorithm with multi-stage optimization is proposed. Experimental results of synthetic images and real images indicate that the proposed algorithm has faster detection speed compared with other methods, and has a high detection accuracy and strong robustness.