Correction of surface error occurring in microlenses characterization performed by optical profilers

Jeremy Béguelin; Torald Scharf; Wilfried Noell; Reinhard Voelkel

doi:10.1117/12.2525693

21 June 2019 Correction of surface error occurring in microlenses characterization performed by optical profilers

Jeremy Béguelin, Torald Scharf, Wilfried Noell, Reinhard Voelkel

Proceedings Volume 11056, Optical Measurement Systems for Industrial Inspection XI; 110560Z (2019) https://doi.org/10.1117/12.2525693
Event: SPIE Optical Metrology, 2019, Munich, Germany

Abstract

Characterizing the surface of microlenses by optical profilers has the important advantages of measurement speed, flexibility and automation. Nevertheless, the accuracy of such characterization is limited by error occurring in non-flat measurements. Here, we propose a method that uses multiple measurements of a single reference ball combined with a machine learning algorithm that fits the experimental data to correct the measurements. The success of the method is demonstrated by showing that the residual error after correction reaches 20 nm RMS. Such results extend greatly the quality of microlens characterization by optical profilers.

Conference Presentation

Citation Download Citation

Jeremy Béguelin, Torald Scharf, Wilfried Noell, and Reinhard Voelkel "Correction of surface error occurring in microlenses characterization performed by optical profilers", Proc. SPIE 11056, Optical Measurement Systems for Industrial Inspection XI, 110560Z (21 June 2019); https://doi.org/10.1117/12.2525693

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