Development of Detection Techniques of Surface Defects for Large Aperture Optical Elements Based on Machine Vision

被引：0

作者：

Tao Xian ^{[1
]}

Zhang Zheng-tao ^{[1
]}

Zhang Feng ^{[1
]}

Shi ya-li ^{[1
]}

Xu De ^{[1
]}

机构：

[1] Chinese Acad Sci, Res Ctr Precis Sensing & Control, Inst Automat, Beijing 100190, Peoples R China

来源：

2014 33RD CHINESE CONTROL CONFERENCE (CCC) | 2014年

关键词：

Large aperture optics; machine vision; dark field imaging; damage detection;

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

This paper describes the status of research and development related to large-aperture optics surface damage detection based on machine vision, which is divided into online and offline systems under dark field imaging mode. The key issues about efficiency, size scaling, sub-image mosaic and adaptability are emphatically discussed in the existence of the detection system. Aiming at those existing problems, this paper outlines a prospect of the development and direction for large-aperture optical element surface damage detection.

引用

页码：2935 / 2940

页数：6

共 11 条

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