Toward the generation of reproducible synthetic surface data in optical metrology

Jesus Pineda; Hernando Altamar-Mercado; Lenny A. Romero; Andrés G. Marrugo

doi:10.1117/12.2558730

19 May 2020 Toward the generation of reproducible synthetic surface data in optical metrology

Jesus Pineda, Hernando Altamar-Mercado, Lenny A. Romero, Andrés G. Marrugo

Proceedings Volume 11397, Dimensional Optical Metrology and Inspection for Practical Applications IX; 113970C (2020) https://doi.org/10.1117/12.2558730
Event: SPIE Defense + Commercial Sensing, 2020, Online Only

Abstract

The implementation and generation of synthetic data for testing algorithms in optical metrology are often difficult to reproduce. In this work, we propose a framework for the generation of reproducible synthetic surface data. We present two study cases using the Code Ocean platform, which is based on Docker and Linux container technologies to turn source code repositories into executable images. i) We simulate interference pattern fringe images as acquired by a Michelson interferometric system. The reflectivity changes due to surface topography and roughness. ii) We simulate phase maps from rough isotropic surfaces. The phase data is simultaneously corrupted by noise and phase dislocations. This method relies on Gaussian-Laplacian pyramids to preserve surface features on different scales. The proposed framework enables reproducible surface data simulations, which could increase the impact of algorithm development in optical metrology.

Conference Presentation

Citation Download Citation

Jesus Pineda, Hernando Altamar-Mercado, Lenny A. Romero, and Andrés G. Marrugo "Toward the generation of reproducible synthetic surface data in optical metrology", Proc. SPIE 11397, Dimensional Optical Metrology and Inspection for Practical Applications IX, 113970C (19 May 2020); https://doi.org/10.1117/12.2558730

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