Open AccessCharacterization of the displacement response in chromatic confocal microscopy with a hybrid radial basis function network
Author(s) -
Wenlong Lu,
Chen Cheng,
Jian Wang,
Richard Leach,
Chi Zhang,
Xiaojun Liu,
Zili Lei,
Wenjun Yang,
Xiangqian Jiang
Publication year - 2019
Publication title -
optics express
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.394
H-Index - 271
ISSN - 1094-4087
DOI - 10.1364/oe.27.022737
Subject(s) - optics , displacement (psychology) , chromatic scale , chromatic aberration , residual , radial basis function , wavelength , radial basis function network , dispersion (optics) , basis (linear algebra) , basis function , physics , algorithm , computer science , mathematics , mathematical analysis , artificial neural network , artificial intelligence , geometry , psychology , psychotherapist
Characterization of the displacement response is critical for accurate chromatic confocal measurement. Current characterization methods usually provide a linear or polynomial relationship between the extracted peak wavelengths of the spectral signal and displacement. However, these methods are susceptible to errors in the peak extraction algorithms and errors in the selected model. In this paper, we propose a hybrid radial basis function network method to characterise the displacement response. With this method, the peak wavelength of the spectral signal is firstly extracted with a state-of-art peak extraction algorithm, following which, a higher-accuracy chromatic dispersion model is applied to determine the displacement-wavelength relationship. Lastly, a radial basis function network is optimized to provide a mapping between the spectral signals and the residual fitting errors of the chromatic dispersion model. Using experimental tests, we show that the hybrid radial basis function network method significantly improves the measurement accuracy, when compared to the existing characterizing methods.