Expand this Topic clickable element to expand a topic
Skip to content
Optica Publishing Group

Automatic Surface Defect Detection Using Autoregressive Modeling-based Fringe Analysis

Not Accessible

Your library or personal account may give you access

Abstract

We propose a novel fringe analysis technique based on an autoregressive (AR) modeling of fringe signals for detecting surface defects. Defects are localized by studying variations in fringe frequencies computed using estimated AR coefficients.

© 2018 The Author(s)

PDF Article
This paper was not presented at the conference

More Like This
Automatic surface defects detection on silicon wafers

N. Miron and D. G. Sporea
CThI51 The European Conference on Lasers and Electro-Optics (CLEO/Europe) 1994

Fringe pattern defect identification using Kalman filter and machine learning

Dhruvam Pandey and Rajshekhar Gannavarpu
W2A.6 Digital Holography and Three-Dimensional Imaging (DH) 2022

Defect localization in noisy fringe patterns using subspace method and naive Bayes classifier

Jagadesh Ramaiah and Rajshekhar Gannavarpu
JTh6A.31 Applied Industrial Spectroscopy (AIS) 2021

Select as filters


Select Topics Cancel
© Copyright 2024 | Optica Publishing Group. All Rights Reserved