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Maximum linear matching: Intelligent and automatic wavelength calibration method
Author(s) -
Yang Lu,
Song Qing,
Wang Zhihui,
Zhang Shihui
Publication year - 2017
Publication title -
concurrency and computation: practice and experience
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.309
H-Index - 67
eISSN - 1532-0634
pISSN - 1532-0626
DOI - 10.1002/cpe.4232
Subject(s) - calibration , computer science , wavelength , spectrometer , pixel , grating , detector , optics , artificial intelligence , set (abstract data type) , computer vision , algorithm , physics , mathematics , statistics , telecommunications , programming language
Summary Wavelength calibration is a necessary means to ensure the normal operation of the spectrometer. In general, calibration light sources that can emit fixed wavelength (such as mercury‐argon lamp) are utilized to generate spectral line on the linear array charge‐coupled device detector. Thus, it is a prerequisite for wavelength calibration to match the pixel position of the well‐divided spectral line with light of different wavelength emitted by calibration light source correctly. In this paper, we aim to present a method to make calibration procedure intelligent and automatic by machine. We establish a pixel‐wavelength model based on bipartite graph and propose the maximum linear matching (MLM) algorithm to find the correct set of pixel‐wavelength automatically. Meanwhile, we calculate precision and recall to measure the effectiveness of MLM and analyze the practical application of MLM by comparing it with conventional artificial methods. Experiments show that the autocalibration method based on MLM can calibrate many types of grating spectrometer more accurately and more reliably. With MLM, we report 98.33% precision and 94.59% recall on 8 groups of experiments.