Optical correlator for textile web defect detection

Nathalie Blanchard; Donald Prevost; Yunlong Sheng

doi:10.1117/12.386806

24 May 2000 Optical correlator for textile web defect detection

Nathalie Blanchard, Donald Prevost, Yunlong Sheng

Proceedings Volume 4089, Optics in Computing 2000; (2000) https://doi.org/10.1117/12.386806
Event: 2000 International Topical Meeting on Optics in Computing (OC2000), 2000, Quebec City, Canada

Abstract

Cost-effective optical correlators are now available for industrial applications. One such application field is the real-time automatic inspection of textile web, in which the high data throughput of the optical correlator over-performs that of the electronic computer. Two approaches for defect enhancement using of wavelet and Wiener filters are proposed. The band-pass wavelet filter is designed to give higher weights in the frequency band, where the energy of defect is higher than that of the web, and to suppress the zero, first and all higher diffracted orders. The Wiener filters are designed based on an average defect shape, with the web texture considered as noise. Using the technique developed at INO (National Optics Institute), a set up of the Vander Lugt type correlator demonstrates experimentally the relevancy of the algorithms. Simulation and optical results are presented.

Citation Download Citation

Nathalie Blanchard, Donald Prevost, and Yunlong Sheng "Optical correlator for textile web defect detection", Proc. SPIE 4089, Optics in Computing 2000, (24 May 2000); https://doi.org/10.1117/12.386806

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available