基于子孔径特征数据集的光学表面疵病拼接方法  

Optical Surface Defect Stitching Method Based on Sub-Aperture Feature Dataset

作　　者：王颖茹 王红军[1] 朱学亮[1] 刘丙才[1] 岳鑫[1] 田爱玲[1] Wang Yingru;Wang Hongjun;Zhu Xueliang;Liu Bingcai;Yue Xin;Tian Ailing(Shaanxi Province Key Laboratory of Thin Films Technology and Optical Test,Xi'an Technological University,Xi'an 710021,Shaanxi,China)

机构地区：[1]西安工业大学陕西省薄膜技术与光学检测重点实验室,陕西西安710021

出　　处：《中国激光》2024年第13期95-104,共10页Chinese Journal of Lasers

基　　金：基础科研项目(JCKY2020426B009);陕西省科技厅秦创原“科学家+工程师”队伍建设项目(2023KXJ-066)。

摘　　要：针对大口径光学元件表面疵病检测中子孔径图像数量较多、在全孔径拼接过程中存储及处理数据量大的问题,提出了一种基于子孔径特征数据集的光学表面疵病拼接方法。该方法由子孔径图像及其重叠区域图像中提取疵病特征数据构建子孔径特征数据集,并通过特征数据集实现子孔径相对位置关系确定及全孔径疵病拼接。通过实验验证,本文方法可以有效实现全孔径疵病目标拼接,并且与基于模板匹配法的全孔径图像拼接方法相比,两种方法获得的全孔径疵病图像的疵病检测结果基本一致,而本文方法在拼接过程中处理的子孔径特征数据集的数据量为3.26 MB,获得的全孔径疵病数据转换出的全孔径疵病图像的数据量为20.9 kB,有效降低了全孔径拼接过程中的处理及存储数据量。Objective With the development of optical technology,the application fields of optical elements and optical systems are becoming increasingly extensive;however,localized microscopic defects on the surface of optics affect the corresponding system performance.Therefore,it is necessary to detect defects on the optical surface.With the development of machine vision technology,the microscopic scattering dark-field imaging method of noncontact detection has become an important method for automated surface defect detection.However,in large-aperture fine optics,there are fewer defects on the surface and a large number of sub-aperture images.When using defect images for sub-aperture stitching,the amount of data used for image storage and processing is high and increases with the size of the detection aperture,which requires a significant amount of time for detection.Accordingly,a surface defect stitching method is proposed based on a sub-aperture feature dataset,which uses the constructed sub-aperture feature dataset to realize full-aperture defect stitching,thereby reducing the amount of data stored and processed during the stitching procedure.Methods To perform full-aperture defect stitching,the defect feature data (defect number,type,shape feature,relative position feature,and sparse matrix data) in the binarized sub-aperture image and its overlapping area image were extracted and the sub-aperture feature dataset could be constructed.Then,based on the constructed feature dataset,for the sub-apertures containing defects in the overlapping areas,the overlapping area matching relationship and the offset parameters between the matched overlapping areas were solved and combined with the initial position calculated from the number of scanning steps of the sub-apertures to obtain an accurate positional relationship between the sub-apertures.For sub-apertures without defects in the overlapping areas,the stitching position was determined based on the theoretical position.Finally,the defect sparse matrix data of each sub-apertu

关 键 词：疵病检测 特征提取 子孔径拼接 稀疏矩阵 

分 类 号：TN247[电子电信—物理电子学]