凸性连通分支搜索的多椭圆检测

Multi-ellipse Detection Based on the Connected Convex Curve Searching

现有的椭圆检测算法如随机霍夫变换,在有遮挡、多目标的情况下存在稳定性差、精度低的缺点。本文提出一种基于凸性连通分支搜索结合曲线拟合的多椭圆检测算法。先按照凸性对边界曲线进行分割,使分割后的曲线符合某一特定的椭圆曲线函数;然后在分割曲线段的基础上进行椭圆拟合;最后合并同一椭圆上的曲线段。对合成图像及自然图像的测试表明,本文提出的方法能够充分利用椭圆曲线边缘点的整体特性,在多椭圆检测中有良好的表现,并具有一定的抗噪性能。

In the multi-ellipse detection especially when they are overlapped, the existing methods such as the Randomized Hough Transform, show drawbacks of poor stability and low accuracy. In this paper, a new methodology was proposed based on the connected convex curve searching and ellipse fitting. Firstly, the edge curve is clustered into different groups by the convexity-leading to each group belonging to a certain ellipse. Secondly, the ellipse fitting is performed on grouped curves. Finally, curves on the same ellipse are merged. Since our method can make full use of properties of ellipse curves, it works well in experiments of both synthetic images and real-word images with a higher accuracy and a certain anti-noise performance