基于有序Hough变换的快速圆检测算法

叶峰; 陈灿杰; 赖乙宗; 陈剑东

doi:10.3788/OPE.20142204.1105

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基于有序Hough变换的快速圆检测算法

信息科学 | 更新时间：2020-08-13

- 基于有序Hough变换的快速圆检测算法
- Fast circle detection algorithm using sequenced Hough transform
- 光学精密工程 2014年22卷第4期页码：1105-1111
- 作者机构：
  
  华南理工大学机械与汽车工程学院,广东广州,中国,510640
- 作者简介：
- 基金信息：
  
  广东省教育部产学研结合项目（No.2012A090300013，No.2012B091100139）();广东省科技计划资助项目（No.2012B011300055）(
- DOI：10.3788/OPE.20142204.1105
  中图分类号： TP391.41
- 收稿日期：2013-08-15，
  
  修回日期：2013-09-22，
  
  纸质出版日期：2014-04-25
- 稿件说明：
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叶峰, 陈灿杰, 赖乙宗等. 基于有序Hough变换的快速圆检测算法[J]. 光学精密工程, 2014,22(4): 1105-1111

YE Feng, CHEN Can-jie, LAI Yi-zong etc. Fast circle detection algorithm using sequenced Hough transform[J]. Editorial Office of Optics and Precision Engineering, 2014,22(4): 1105-1111
叶峰, 陈灿杰, 赖乙宗等. 基于有序Hough变换的快速圆检测算法[J]. 光学精密工程, 2014,22(4): 1105-1111 DOI： 10.3788/OPE.20142204.1105.

YE Feng, CHEN Can-jie, LAI Yi-zong etc. Fast circle detection algorithm using sequenced Hough transform[J]. Editorial Office of Optics and Precision Engineering, 2014,22(4): 1105-1111 DOI： 10.3788/OPE.20142204.1105.

摘要

针对随机Hough变换（RHT）及其改进算法在同一圆边缘点随机抽样时命中率低且投票处理过程复杂，提出了基于有序搜索的广义Hough变换快速圆检测算法（SQHT）。该算法利用圆的几何性质和梯度方向信息来有序搜索圆边缘点集，将Hough变换的基于投票判定基元参数转变为有效确定基元三点的讨论。执行算法时，首先顺序搜寻第一边缘点并根据邻域边缘点集或图像灰度值计算其梯度值；接着在第一点所在行匹配与其梯度信息相符的第二点，根据前两点信息在第一点所在列匹配第三点；最后按照RHT算法流程确定有效基元参数，从而避免了随机抽样带来的时间不确定性。该算法具有计算速度快，检测时间可控，适用范围广泛，抗干扰性强等特点。相比于RHT算法，提出的算法在单目标圆检测情况下检测效率提高了2倍，在多目标圆（5个及以上）且有非目标边缘点情况下检测效率提高了5倍，在多圆检测方面能有效弥补了Hough变换算法的不足。

Abstract

To solve the problem of low hit ratio of random sampling in the same circle and complexity of voting process when Randomized Hough Transform (RHT) or its improved algorithm were used to detect circles

an algorithm for fast circle detection using Sequenced Hough Transform (SQHT) was proposed. It used the geometric features and gradient direction information of a circle to sequentially search the circle edge points sets and turned the acquisition of circle parameters based on vote of RHT to a discussion of locating three points of circle effectively. By using the method

the first edge point was searched sequentially and its gradient was calculated based on the adjacent edge point set or its gray value. The second point was mapped according to gradient of the first point in the row. The third point was mapped according to the information of two points above. The true circle parameters were finally calculated by RHT method

which avoids timing uncertainty caused by randomness of sampling. This method has features of high speed

controllable detection time

wide range of application and strong anti-interference performance. Comparing with the RHTs

experimental results indicate that the proposed algorithm can improve 2 times or more in the image of single circle

and 5 times or more in the image of multi-circles (5 or more). It can efficiently remedy the shortage of RHT in multi-circle detection.

关键词

Keywords

references

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