Precise microscopic profilometry using diffractive image correlation and theoretical model simulation

Guo-Wei Wu; Ming-Jun Jiang; Liang-Chia Chen

doi:10.1117/12.2528597

3 September 2019 Precise microscopic profilometry using diffractive image correlation and theoretical model simulation

Guo-Wei Wu, Ming-Jun Jiang, Liang-Chia Chen

Proceedings Volume 11102, Applied Optical Metrology III; 111020A (2019) https://doi.org/10.1117/12.2528597
Event: SPIE Optical Engineering + Applications, 2019, San Diego, California, United States

Abstract

This work presents a novel microscopic profilometry using diffraction image correlation, which is appropriate for in-situ automated optical inspection (AOI). In contrast to the traditional confocal microscopy, the developed technique replaces the detector pinhole by observing and matching the diffraction patterns. Thus accurate surface depth detection can be achieved by eliminating time-consuming vertical scanning operation. The development is the first attempt in optics to use image correlation between the pre-calibrated database of diffraction images and the measured one of the detecting object surface. The feasibility of the method has been theoretically verified by scalar diffraction theory, then verified by experimental testing. Also, a depth response curve with the physical meaning of similarity is introduced and interpreted. Meanwhile, multi-point lateral scanning in one field of view (FOV) is achieved by quickly switching micromirrors on the digital micromirror device (DMD), thus the quasi full-field 3-D reconstruction can be acquired by combining tens of captured images. Verified experimentally, a 3-D reconstruction with sub-micrometer vertical resolution can be realized, with a tunable lateral resolution.

Conference Presentation

Citation Download Citation

Guo-Wei Wu, Ming-Jun Jiang, and Liang-Chia Chen "Precise microscopic profilometry using diffractive image correlation and theoretical model simulation", Proc. SPIE 11102, Applied Optical Metrology III, 111020A (3 September 2019); https://doi.org/10.1117/12.2528597

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