Adaptive modal decomposition based overlapping-peaks extraction for thickness measurement in chromatic confocal microscopy
Year: 2020
Type: article
Abstract: Accurate overlapping-peaks extraction plays a critical role in chromatic confocal thickness measurement of ultra-thin transparent film. However, the current algorithms usually appear as a perceptible extraction error resulting from the disturbing influence among peaks in the process of fitting the spectral axial response signal (sARS) of the two measuring surfaces. In this paper, we propose an adaptive modal decomposition method to extract multi peaks for the ultra-thin materials. With this method, the sARS can be firstly decomposed into several sub-modes, which can be used to obtain the peak wavelength of each measuring surface by the existing single peak extraction algorithms, such as the centroid method and Gauss fitting method. Monte Carlo simulations and experimental tests demonstrate that the proposed algorithm has significant improvements over the existing nonlinear fitting algorithms in terms of peak extraction accuracy and precision.
Source: Optics Express
DOI: 10.1364/oe.410177
Authors: Jiafu Li, Yanlong Zhao, Hua Du, Xiaoping Zhu, Kai Wang, Mo Zhao
Language: English
Subfield: Computer Vision and Pattern Recognition
Field: Computer Science
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $2,270
Award: G4362194837
OpenAlex ID: W3097765545
