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Volume 37 Issue 2
Jan.  2013
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Improved polynomial iterative fitting algorithm for baseline correction in infrared spectroscopy

  • Corresponding author: WANG Zhi-bin, zhibin_wang@126.com
  • Received Date: 2012-06-14
    Accepted Date: 2012-08-16
  • Baseline correction is an important preprocessing step before subsequent data processing of Fourier transform infrared (FTIR) spectra. Polynomial iterative fitting is one of the methods of baseline correction. In order to improve the speed of baseline correction, taking CO2 spectrum as example, an improved polynomial iterative fitting algorithm was used for theoretical analysis and experimental verification and the same correction result was achieved with polynomial iterative fitting algorithm.The algorithm automatically identify the range of peaks for baseline correction, reducing the number of iterations in the process of baseline correction. The number of iterations decreased from 39 to 11, the elapsed time reduced from 4.78s to 1.12s. The result is great significant for real-time gas monitoring systems.
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    沈阳化工大学材料科学与工程学院 沈阳 110142

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Improved polynomial iterative fitting algorithm for baseline correction in infrared spectroscopy

    Corresponding author: WANG Zhi-bin, zhibin_wang@126.com
  • 1. Engineering Technology Research Center of Shanxi Province for Opto-Electronic Information and Instrument, North University of China, Taiyuan 030051, China;
  • 2. Key Laboratory of Instrumentation Science & Dynamic Measurement, Ministry of Education, North University of China, Taiyuan 030051, China

Abstract: Baseline correction is an important preprocessing step before subsequent data processing of Fourier transform infrared (FTIR) spectra. Polynomial iterative fitting is one of the methods of baseline correction. In order to improve the speed of baseline correction, taking CO2 spectrum as example, an improved polynomial iterative fitting algorithm was used for theoretical analysis and experimental verification and the same correction result was achieved with polynomial iterative fitting algorithm.The algorithm automatically identify the range of peaks for baseline correction, reducing the number of iterations in the process of baseline correction. The number of iterations decreased from 39 to 11, the elapsed time reduced from 4.78s to 1.12s. The result is great significant for real-time gas monitoring systems.

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