为了提高数字图像中椭圆检测的效率和准确性,提出了一个基于最小二乘法的改进的随机椭圆检测算法.

该算法随机选取图像中的3 个边缘点,在以这3 个点为中心的窗口内,从边缘点中拟合出可能椭圆,并通过随机选

取的第4 个边缘点来确认可能椭圆. 利用直接最小二乘法椭圆拟合的特性,引入可能椭圆边缘点收集和椭圆重新

拟合的迭代过程来提取最终的椭圆参数. 通过对含有不同噪声的仿真图片和包括残缺椭圆的实际图片的实验表

明,新算法的改进是有效的. 与原算法相比,新算法降低了对参数的依赖性,提高了检测的速度、稳定性和准确性,

同时保留了原算法的抗噪声能力.-: An imp roved randomized ellip se detection algorit hm based on least square approach was proposed

to enhance t he efficiency and accuracy of ellip se detection in digital images. This algorit hm randomly se2

lect s three edge point s in t he image , and t hen uses least square approach to fit all t he edge point s in three

windows , which are defined by t he t hree edge point s. The forth edge point is randomly selected to judge

whet her a possible ellip se exist s in t he image. Utilizing the characteristic of direct least square fit ting of

ellip se , an iteration process of edge point collecting and ellip se refit ting of possible ellip se was int roduced

to ext ract t he final ellip se’s parameters. Artificial images wit h different level s of noise and nature images

containing incomplete ellip ses were employed to test t his algorithm. Experimental result s show that t he

improvement s are notable. Compared with the original algorit hm , t he propo sed algorit hm reduces