基于边界曲线弧分割的多椭圆检测

不同于传统的Hough变换算法，提出一种基于边界弧分割的椭圆检测方法。首先将边界从交点处分割成弧段，将得到弧段划分为长弧和短弧两组并按长度降序排序，然后从两组中找出属于某个椭圆的若干弧段，利用最小二乘法拟合得到候选椭圆并验证是否为真正椭圆。实验表明该算法能快速检测出图中椭圆，运行时间远小于采用随机Hough变换算法，在具有噪声、椭圆残缺的情况下仍能有较好的检测结果。

Multiple ellipses detection based on curve arc segmentation of edge

In this paper, a new efficient algorithm for ellipse detection was proposed, which was based on edge grouping, different from standard Hough transform. Firstly, It separated edge boundary into different arcs at the intersections, divided those arcs into two categories: the long and the short and sorted the two categories at non-increasing sequence, then estimated the parameters of the ellipses using least square fitting method with arcs which may belong to the same ellipse; at last testified whether ellipses coming from the front steps are real ones. The method has been tested on synthetic and real-world images containing both complete and incomplete ellipses. The outcome demonstrates that the algorithm is robust, accurate and effective.