阈值迭代的单目视觉系统中像点质心定位

doi:10.13229/j.cnki.jdxbgxb20190411

摘要/Abstract

摘要：

针对大尺寸单目视觉坐标测量系统中二维像点的亚像素定位精度对三维坐标测量精度影响较大的问题，就光学特征点在像平面上的二维像点质心定位方法进行了分析。基于针孔成像原理建立了摄像机模型，讨论了光学特征点对应的二维像点的提取方法，重点研究了二维像点的亚像素定位。提出了基于阈值迭代的像点质心定位方法，该算法通过设置阈值并多次迭代，减小成像对称性差带来的误差；通过三次插值算法，增加参与定位计算的成像中心周围的有效像素点；通过灰度平方加权算法，增加灰度值大的像素点在定位计算中的权重，减小噪声误差。对比实验表明：本文提出的像点质心定位算法可实现1/100以上的像素细分。本文算法在x和y方向的定位标准差分别为0.0022和0.0019 pix，与灰度平方加权质心定位法和双三次插值灰度平方加权质心定位法相比均更小，定位精度更高。x和y方向的定位误差范围分别在0.0039和0.0046 pix以内,与前两种方法相比均更小，定位稳定性更好。本文提出的定位方法可应用于各类近圆形小光源图像的区域亚像素定位。

关键词: 仪器仪表技术, 视觉测量, 质心定位, 灰度值, 插值算法, 阈值

Abstract:

The sub-pixel positioning accuracy of 2D image points in the large-sized single camera vision coordinate measurement system has a great influence on the accuracy of 3D coordinate measurement. To solve this problem this paper analyzes the centroid localization method of the optical feature points on the image plane. Based on the principle of pinhole imaging, the camera model is established. The extraction method of 2D image points corresponding to optical feature points is discussed, and the sub-pixel positioning of 2D image points is studied in depth. A centroid localization algorithm based on threshold iteration is proposed. This algorithm increases the number of effective pixels around the imaging center of the optical feature points by interpolation algorithm. It reduces the noise error by gray-scale square weighting. By setting the threshold value and several iterations, the error caused by asymmetry of the characteristic spot can be reduced, so as to realize the accurate positioning of the feature points. Through comparative experiments, it is proved that the positioning algorithm proposed in this paper can realize 1/100 pixel subdivision of the image point or more. The positioning standard deviation of the proposed algorithm in the direction of x and y is 0.0022 pix and 0.0019 pix respectively. Compared with gray square weighted centroid positioning method and double cubic interpolation gray square weighted centroid positioning method, the positioning standard deviation of the proposed algorithm is smaller, and the proposed algorithm has higher positioning accuracy. The positioning errors of x and y directions are within the range of 0.0039 pix and 0.0046 pix respectively, which are smaller than the previous two methods, and the proposed algorithm has better positioning stability. The localization method proposed in this paper can be applied to the sub-pixel localization of various near-circular small light source images.

Key words: technologyof instrument and meter, visual measurement, centroid localization, gray value, interpolation algorithm, threshold

中图分类号:

TH741

周婧,张小宝,白云龙,侯丽新. 阈值迭代的单目视觉系统中像点质心定位[J]. 吉林大学学报(工学版), 2020, 50(5): 1796-1801.

Jing ZHOU,Xiao-bao ZHANG,Yun-long BAI,Li-xin HOU. Centroid location of image points in single camera vision measurement system with threshold iteration[J]. Journal of Jilin University(Engineering and Technology Edition), 2020, 50(5): 1796-1801.

图/表 7

图1

图2

图3

图4

表1

表2

标准差比较结果"

项目	灰度平方加权算法	双三次插值灰度平方加权算法	本文算法
质心坐标 $x ˉ$	245.27	245.32	245.26
质心坐标 $y ˉ$	313.78	313.37	313.67
$x$ 方向标准差	0.0039	0.0023	0.0022
$y$ 方向标准差	0.0033	0.0024	0.0019

表2

图5

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