A Real-Time Peak Extraction Algorithm for Dynamic Displacement Measurement Based on Spectral Confocal Microscopy

Abstract

Abstract Spectral confocal is widely used in various fields such as topography detection, roughness measurement, thickness measurement, for its advantages ability in displacement measurement. Developed from confocal microscopy, the spectral confocal microscopy greatly improves the efficiency of displacement measurement because there is no need for longitudinal scanning, In other words, we need to obtain the wavelength information corresponding to the peak point of the spectral signal, which is called peak abscissa but not the peak value. Therefore, Accurate and efficient peak abscissa calculation algorithm occupies an important position in displacement monitoring based on spectral confocal. However, the existing methods are too complex to apply to real-time dynamic online detection, for they usually focus on determining the peak value by means of curve fitting and peak extraction. In this paper, we proposed an efficient and accurate peak abscissa calculation method by shifting, difference, linear fitting, zero point and peak abscissa calculation (SDLZ). Compared with the Gaussian fitting method, the results demonstrate that the SDLZ can greatly improve efficiency, can be applied to field programmable gate array microcontrollers, with high measurement accuracy, providing key solutions for equipment needs.