Title :
Automatically Detecting Peaks in Terahertz Time-Domain Spectroscopy
Author :
Stephani, Henrike ; Jonuscheit, Joachim ; Robine, Christoph ; Heise, Bettina
Author_Institution :
Fraunhofer ITWM & Tech. Univ., Kaiserslautern, Germany
Abstract :
To classify spectroscopic measurements it is necessary to have comparable methods of evaluation. In Terahertz (THz) time-domain spectroscopy, as a new technology, neither the presentation of the data nor the peak detection is standardized yet. We propose a procedure for automatic peak extraction in THz spectra of chemical compounds. After preprocessing in the time-domain, we use a variance based algorithm for determining the valid frequency region. We furthermore propose a baseline correction using simulated THz spectra. We illustrate how this procedure works on the example of hyperspectral THz measurements of six chemical compounds. Subsequently we propose to use unsupervised classification on the thus processed data to robustly detect the characteristic peaks of a compound.
Keywords :
chemical variables measurement; pattern classification; terahertz spectroscopy; THz spectra; automatic peak detection; chemical compounds; spectroscopic measurements; terahertz time-domain spectroscopy; unsupervised classification; Chemical compounds; Databases; Frequency domain analysis; Noise; Shape; Spectroscopy; Time domain analysis; Feature extraction reduction and analysis; Signal processing systems and applications; Signal/image representation;
Conference_Titel :
Pattern Recognition (ICPR), 2010 20th International Conference on
Conference_Location :
Istanbul
Print_ISBN :
978-1-4244-7542-1
DOI :
10.1109/ICPR.2010.1085