Detection of arc surface defects in microscope lens detection system

GUO Qing-hua; LIU Hai-xia; Song Li-mei; XI Jiang-tao

doi:10.3788/OPE.20152313.0791

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Detection of arc surface defects in microscope lens detection system

更新时间：2020-08-13

- Detection of arc surface defects in microscope lens detection system
- Optics and Precision Engineering Vol. 23, Issue 10z, Pages: 790-797(2015)
- 作者机构：
  
  1. 天津工业大学电气工程与自动化学院电工电能新技术重点实验室, 天津 300160
  2. 澳大利亚伍伦贡大学电气计算机和通信工程学院, 澳大利亚 2500
- 作者简介：
- 基金信息：
- DOI：10.3788/OPE.20152313.0791
  CLC： TH742.9;TP391.4
- Received：02 June 2015，
  
  Revised：20 June 2015，
  
  Published：14 November 2015
- 稿件说明：
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郭庆华, 刘海霞, 宋丽梅等. 显微镜镜头的圆弧表面缺陷检测[J]. 光学精密工程, 2015,23(10z): 790-797

GUO Qing-hua, LIU Hai-xia, Song Li-mei etc. Detection of arc surface defects in microscope lens detection system[J]. Editorial Office of Optics and Precision Engineering, 2015,23(10z): 790-797
郭庆华, 刘海霞, 宋丽梅等. 显微镜镜头的圆弧表面缺陷检测[J]. 光学精密工程, 2015,23(10z): 790-797 DOI： 10.3788/OPE.20152313.0791.

GUO Qing-hua, LIU Hai-xia, Song Li-mei etc. Detection of arc surface defects in microscope lens detection system[J]. Editorial Office of Optics and Precision Engineering, 2015,23(10z): 790-797 DOI： 10.3788/OPE.20152313.0791.

摘要

针对微型显微镜镜头存在的圆弧表面缺陷

提出了一套圆弧表面缺陷检测系统

以提高镜头的表面质量。在传统的图像边缘检测中

加入了图像预处理和边缘检测的方法

更好地实现了对目标的轮廓提取。然后

利用面向对象的VC++编程工具结合图像检测方法

对提取到的合格镜头和缺陷镜头同时进行图像处理

以找出缺陷镜头圆弧的瑕疵。最后

根据同时对合格镜头和缺陷镜头进行图像处理取得的结果

判断合格与缺陷镜头的差别

提取出缺陷镜头的圆弧表面特征轮廓。实验结果表明:设计的系统的像素精度为5.37

缺陷检测精度为96%

能够实现对微型显微镜镜头圆弧表面的边缘提取与检测。

Abstract

A detection system for arc surface defects of the microscope lens was proposed to improve the manufacturing quality of the lens. The image preprocessing and image edge detection were introduced the morphological operations to realize the contour extraction of a target. The image preprocessing and edge detection were added into the traditional edge detection. Then

VC ++ object-oriented programming tools were combined with the image detection for simultaneously processing the qualified lens and the defect lens to find out the faults of the defect lens. Finally

according to the results from the image processing for qualified lens and the defect lens

the difference between the qualified and the defect lenses is judged

thus the arc surface characteristic contour of the defect lens was extracted. The experimental results show that the accuracy of the designed system is 5.37

m and the accuracy of the defect detection is 96%. The system can realize the edge extraction and edge detection of arc surface of the microscope lens.

关键词

Keywords

references

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