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Updated: Jun 30, 2026

ARL Spectral Fitting as an Application to Augment Spectral Data via Franck-Condon Lineshape Analysis and Color Analysis
Published on: August 19, 2021
[A method for automatic recognition of stellar spectra based on feature matching of spectral lines]
Zhong-tian Liu1, Kuan-min Qiu, Rui-zhen Zhao
1School of Electronics and Information Engineering, Beijing Jiaotong University, Beijing 100044, China. liuzht@bjtu.edu.cn
Abstract:
The LAMOST project, the world's largest sky survey project being implemented in China, urgently needs an automatic stars recognition system. The present paper presents a method for automatic recognition of stellar spectra based on feature matching of spectral lines. This method consists of three main steps: First, the features of spectral lines! in the observed spectra are extracted using the wavelet transform. Then, the correlations between the extracted features and the feature templates of the stellar spectral lines are computed. Finally, based on the results of the former step, the stellar spectra can be recognized. The extensive experiments with real observed spectra from the SDSS DR4 show that the method can robustly recognize stellar spectra, and the correct rate of this method is as high as 96.7%. This method is designed to automatically recognize stellar spectra with relative flux and low signal-to-noise ratio, which is applicable to the LAMOST data and helps in the structure study of stars and galaxy etc.
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