光刀自适应灰度加权亚像素中心精确提取

胡改玲 1; 周翔 1; 杨涛 1; 王军平 1; 张春伟 1; 王刚锋 2; 李玉勤 1; 郭家玉 1

doi:10.7652/xjtuxb201805003

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光刀自适应灰度加权亚像素中心精确提取

更新时间：2025-07-09

- 光刀自适应灰度加权亚像素中心精确提取
- Sub-Pixel Centerline Extraction Based on Light Stripe Adaptive Grayscale Weighting
- 西安交通大学学报 2018年52卷第5期页码：21-28
- 作者机构：
  
  西安交通大学机械工程学院,西安,710049
- 作者简介：
- 基金信息：
  
  : 2017-08-11.作者简介: 胡改玲(1984—),女,博士生;周翔(通信作者),男,副教授。基金项目: 国家自然科学基金资助项目(51575437)
- DOI：10.7652/xjtuxb201805003
  中图分类号： TN911.73
- 网络首发：2018-05-10，
  
  纸质出版：2018
- 稿件说明：
移动端阅览
胡改玲 1, 周翔 1, 杨涛 1, 等. 光刀自适应灰度加权亚像素中心精确提取[J]. 西安交通大学学报, 2018,52(5):21-28.

Sub-Pixel Centerline Extraction Based on Light Stripe Adaptive Grayscale Weighting[J]. 2018, 52(5): 21-28.
胡改玲 1, 周翔 1, 杨涛 1, 等. 光刀自适应灰度加权亚像素中心精确提取[J]. 西安交通大学学报, 2018,52(5):21-28. DOI： 10.7652/xjtuxb201805003.

Sub-Pixel Centerline Extraction Based on Light Stripe Adaptive Grayscale Weighting[J]. 2018, 52(5): 21-28. DOI： 10.7652/xjtuxb201805003.

摘要

为了提高线结构光三维面形测量精度

提出了一种基于骨架跟踪的光刀法向自适应灰度加权中心提取方法。首先由采集的光刀图像根据数学形态学方法计算得到一组光滑、单向连通的光刀骨架

以骨架为搜索路径

沿骨架法向设置一个有用像素区域。根据骨架法向截面内像素灰度对光刀中心提取影响的重要程度划分不同的灰度阈值

对影响中心提取较大的像素灰度值进行加权平方

最后根据灰度加权重心法计算光刀亚像素中心。分别通过仿真实验与多组真实光刀中心提取实验进行验证

仿真结果表明

本文算法提取到的光刀中心到拟合曲线距离的平均偏差小于0.3像素

标准偏差小于0.03像素

计算时间为87.6 ms。实物测量结果表明

用本文方法提取光刀中心时最大偏差距离、平均偏差距离和标准偏差较其他方法最小

提取结果稳定、精度高、鲁棒性好

能得到光顺性较好的亚像素光刀中心线

满足在线测量的要求。

Abstract

This paper presents a method of adaptive grayscale weighted center extraction of light stripe based on skeleton tracking in order to improve the linear structured light three-dimensional surface measurement accuracy. First

a set of fairing and unidirectional skeletons is calculated by mathematical morphological method from the acquired images. Taking the skeleton as a search path

a useful pixel region is set along the normal direction of the skeleton. The grayscale threshold is divided according to the degree of importance of pixel grayscale on the light stripe centerline extraction in the normal section of the skeleton. The value of pixel gray which is more important to centerline extraction is weighted square. Then

the sub-pixel center of the light stripe is calculated according to the gray weighted centroid method. Finally

simulations and experiments are carried out. The simulation results show that the average deviation from the centerline of the light tripe to the fitted curve is less than 0.3 pixels

the standard deviation is less than 0.03 pixels

and the calculation time is 87.6 ms. The experimental results show that the maximum deviation

average deviation and standard deviation extracted by this method are all smaller compared with other methods. The proposed method has some advantages

including high accuracy

stable extraction result and good robustness

whereby a sub-pixel light stripe centerline with fine fairness can be obtained and hence the online measurement requirements could be satisfied.

关键词

Keywords

references

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