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.