[1]王赛赛,周阿维.基于 Canny-Harris 角点检测的光学元件表面疵病检测[J].机械与电子,2024,42(08):26-34.
　WANG Saisai,ZHOU Awei.Surface Defect Detection of Optical Components Based on Canny-Harris Corner Detection[J].Machinery & Electronics,2024,42(08):26-34.
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基于 Canny-Harris 角点检测的光学元件表面疵病检测()
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《机械与电子》[ISSN:1001-2257/CN:52-1052/TH]

卷:
42
期数:
2024年08期
页码:
26-34
栏目:
自动控制与检测
出版日期:
2024-08-31

文章信息/Info

Title:
Surface Defect Detection of Optical Components Based on Canny-Harris Corner Detection
文章编号:
1001-2257 ( 2024 ) 08-0026-08
作者:
王赛赛; 周阿维
西安工程大学机电工程学院,陕西 西安 710600
Author(s):
WANG Saisai ;  ZHOU Awei
( College of Mechanical and Electrical Engineering , Xi ’an Polytechnic University , Xi ’an 710600 , China )
关键词:
光学元件; 疵病检测; Canny-Harris 算法; 图像拼接; 疵病识别
Keywords:
optical component ;  defect detection ;  Canny-Harris algorithm ;  image stitching ;  defect recognition
分类号:
TH741 ; TP391.41
文献标志码:
A
摘要:
为提高光学元件表面疵病检测的准确性,提出了一种基于 Canny-Harris 角点检测的光学元件表面疵病检测方法。该方法首先利用基于迭代式阈值的 Canny 算子对图像进行边缘检测,得到候选角点;接着,利用基于局部窗口角点密度的可变窗口非极大值抑制方法去除候选角点中的伪角点,以得到检测精度更高的 Canny-Harris 角点检测算法;然后,利用 Canny-Harris 角点检测算法进行图像拼接,并利用边界测定法提取出拼接图像中的疵病特征;最后,通过计算疵病的形状因子,实现对疵病的分类。实验结果表明,该方法能够成功实现子孔径图像的精确拼接,并准确地检测出光学元件表面疵病信息。
Abstract:
To improve the accuracy of surface defect detection of optical components , a method for detecting surface defects of optical components based on Canny-Harris corner point detection is proposed. Firstly , the Canny operator based on iterative threshold is used to detect the edge of the image to obtain candidate corner points , so as to reduce the calculation amount of the algorithm ; then , the variable window non-maximum suppression method based on local window corner point density is used to remove the pseudo corner points in the candidate corner points to obtain the correct corner points ; then , the detected corner points are used for image stitching , and the defective features in the stitched images are extracted by boundary determination method ; finally , defect classification is achieved through the calculation of the defect ’s shape factor.Experimental results show that this method can successfully achieve the accurate stitching of sub-aperture images and accurately detect the surface detect information of optical components.

参考文献/References:

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备注/Memo

备注/Memo:
收稿日期: 2023-11-16
基金项目:陕西省自然科学基础研究计划资助项目( 2018JQ5180 )
作者简介:王赛赛 ( 1997- ),男,安徽淮北人,硕士研究生,研究方向为质量检测、图像处理;周阿维 ( 1981- ),女,陕西西安人,博士,副教授,硕士研究生导师,研究方向为零件质量非接触检测。
更新日期/Last Update: 2024-09-02