In spectroscopy data analysis, such as Raman spectra, X-ray diffraction, fluorescence and etc., baseline drift is a ubiquitous issue. In high speed testing which generating huge data, automatic baseline correction method is very important for efficient data processing. We will survey the algorithms from classical Shirley background to state-of-the-art methods to present a summation for this specific field. Both advantages and defects of each algorithm are scrutinized. To compare the algorithms with each other, experiments are also carried out under SVM gap gain criteria to show the performance quantitatively. Finally, a rank table of these methods is built and the suggestions for practical choice of adequate algorithms is provided in this paper.