Efficient and precise detection for surface flaws on large-aperture optics based on machine vision and machine learning
Authors:
- Zhaoyang YinZYZhaoyang Yin
- Henan LiuHLHenan Liu
- Linjie ZhaoLZLinjie Zhao
- Jian ChengJCJian Cheng
- Chao TanCTChao Tan
- Xiaotao LiXLXiaotao Li
- Yankang ChenYCYankang Chen
- Zhiyu LinZLZhiyu Lin
- Mingjun ChenMCMingjun Chen
- 10 December 2022
- journal article
- research article
- Published by Elsevier in Optics & Laser Technology
- Vol. 159
Abstract
No abstract availableKeywords
This publication has 33 references indexed in Scilit:
- A Novel and Effective Surface Flaw Inspection Instrument for Large-Aperture Optical ElementsIEEE Transactions on Instrumentation and Measurement, 2015
- No-reference image quality assessment based on spatial and spectral entropiesSignal Processing: Image Communication, 2014
- Defect inspection and extraction of the mobile phone cover glass based on the principal components analysisThe International Journal of Advanced Manufacturing Technology, 2014
- Analysis of focus measure operators for shape-from-focusPattern Recognition, 2013
- A Survey on Various Edge Detector TechniquesProcedia Technology, 2012
- Defect classification using machine learning2008
- The effect of laser pulse duration on laser-induced damage in KDP and SiO 22006
- Growth of laser damage on the input surface of SiO 2 at 351 nm2006
- Large lenses, mirrors, and filters for astronomy2004
- Mapping and inspection of damage and artifacts in large-scale optics1998