基于中心估计的椭圆检测

椭圆检测在图像理解中有重要的作用。为克服标准Hough变换对时空需求高的缺点，设计了一种改进算法。通过椭圆对称特性估计图像中可能存在的椭圆中心，利用长轴确定椭圆中心及夹角参数只需一维累积数组对椭圆短轴的投票，采用聚类分析技术将检测到的虚椭圆归类到对应的真实椭圆。对合成图像和实际图像的实验表明算法的正确和高效。

Ellipse detection based on center estimation

A fast automatic detection of ellipses is very important for the understanding of some images.In order to overcome the excessive time and storage requirements associated with the Hough transform,we introduce an improved algorithm.This algorithm uses geometric symmetry to estimate the potential centers of ellipses.It also takes the advantages of major axis of an ellipse to find center and orientation parameters of the ellipse,and uses an one-dimensional accumulator array to accumulate the length of minor axis of the ellipse.By using data clustering,it classifies all detected virtual ellipses into their corresponding real ellipses.Experiments with both synthetic and real images indicate the correctness and effectiveness of the proposed algorithm.