摘要
针对传统圆检测算法检测速度慢、不适于多圆检测的问题,提出一种基于全局搜索的圆检测方法。将证据积累和加权平均的思想结合,对证据积累过程中产生的伪圆心进行归类、分析,并对三类伪圆心进行逐类剔除,最后计算其它圆参数。实验结果表明,该算法效率高,对局部信息缺损不敏感,检测时间不会随着圆个数的增加而线性增加,检测效果明显优于传统的随机圆检测(RCD)算法。
Aiming at solving the problem that the traditional circle detection algorithm is characterized by low detection speed and so is unfit for multi-circle detection,a circle detection method based on global searching is proposed. By combining the accumulation of evidence with weighted average,the pseudo-center of a circle produced in the process of accumulation of evidence is classified and analyze,then 3 pseudo-centers of a circle kind by kind are rejected and the other circle parameters are computed. The experimental results show that the proposed algorithm is of high efficiency and is not sensitive to the defect of local information. And the detection time will not increase linearly with the numbers of circle and the detection result is better than the traditional random circle detection （RCD） algorithm obviously.
出处
《光学学报》
EI
CAS
CSCD
北大核心
2010年第9期2608-2612,共5页
Acta Optica Sinica
基金
国防科工委"十一五"重点项目(B20301118)资助课题
关键词
机器视觉
圆检测
证据积累
全局搜索
machine vision
circle detection
evidence accumulation
global search
