Auto-Focusing of Ultra-clean Sample Based on Projection View Method

被引：3
作者：
Liu, Xing [1 ,2 ]
Chen, Guodong [1 ,2 ]
Zheng, Jinlun [1 ,2 ]
Wei, Jingsong [1 ,2 ]
机构：
[1] Chinese Acad Sci, Shanghai Inst Opt & Fine Mech, Lab Micronano Optoelect Mat & Devices, Shanghai 201800, Peoples R China
[2] Univ Chinese Acad Sci, Ctr Mat Sci & Optoelect Engn, Beijing 100049, Peoples R China
来源：
TWELFTH INTERNATIONAL CONFERENCE ON INFORMATION OPTICS AND PHOTONICS (CIOP 2021) | 2021年 / 12057卷
基金：
中国国家自然科学基金;
关键词：
Auto-focusing; Projection view; Ultra-clean sample;
D O I：
10.1117/12.2606335
中图分类号：
O43 [光学];
学科分类号：
070207 ; 0803 ;
摘要：
Auto-focusing methods, including infrared ranging, laser triangulation, ultrasound distance measurement, contrast detection, phase detection, depth from defocus, and depth from focus, are widely applied in laser direct writing system. Concurrently, the samples with an ultra-clean surface may cause the focusing to fail. This paper presents a method based on projection view to solve the auto-focusing problem of ultra-clean sample. A projection view in the Koller illumination path, is projected to the focal plane of the objective lens. One can, use the image of projection view in the charge coupled device (CCD) to evaluate the image definition so as to conduct a fast and accurate auto-focusing. A gray variance fusion model used for focusing accuracy evaluation is proposed. The robustness and accuracy of the auto-focusing are measured experimentally. The influencing factors including illumination condition and sample materials are analyzed. This method is useful for auto-focusing of ultra-clean samples.
引用
收藏
页数：7
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