Detection in Raman Spectroscopy Data

Raman spectroscopy has been shown to be a powerful technique for non-contact and non-destruction detections and identifications. It uses a laser to probe the vibrational energy levels of a molecule or crystal, and thus provides information on molecular structure and chemical composition of materials.
Raman library Spectra
A Raman spectrum gives a set of peaks that correspond to the characteristic vibrational frequencies of the material, which can be used as a signature for identification of various materials. We develop algorithms for detection of surface-deposited chemical agents that provide robust performance to different operating and environmental conditions.

Active Project:

    Algorithm Development for Standoff Raman Spectroscopy Data
    Funded by the US Army Research, Development and Engineering Command (RDECOM)

Project team:

Recent publications:

  • W. Wang, T. Adali, and D. Emge, "Subspace partitioning for target detection and identification," IEEE Trans. Signal Processing, vol. 57, no. 4, April 2009.
  • W. Wang and T. Adali, "Detection using correlation bound in a linear mixture model," Signal Processing, vol. 87, pp. 1118-1127, 2007.
    • An unsupervised detection method using canonical correlation analysis is introduced for Raman spectroscopy. Simulation and experimental results are presented to demonstrate the effectiveness of the proposed method.
  • H. Li, T. Adali, W. Wang, D. Emge, and A. Cichocki, “Non-negative matrix factorization with orthogonality constraints and its application to Raman sctroscopy,” VLSI Signal Processing Systems for Signal, Image, and Video Technology, vol. 48, nos. 1-2, pp. 83-97, August 2007.
    • We introduce a class of algorithms for non-negative matrix factorization using orthogonality constraints and show their application to detection of a target spectrum in Raman spectra data.

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