  Raman spectroscopy is a powerful and non-invasive method for analysis of
chemicals and detection of unknown substances. However, Raman signal is so weak
that background noise can distort the actual Raman signal. These baseline
shifts that exist in the Raman spectrum might deteriorate analytical results.
In this paper, a modified version of active contour models in one-dimensional
space has been proposed for the baseline correction of Raman spectra. Our
technique, inspired by principles of physics and heuristic optimization
methods, iteratively deforms an initialized curve toward the desired baseline.
The performance of the proposed algorithm was evaluated and compared with
similar techniques using simulated Raman spectra. The results showed that the
1D active contour model outperforms many iterative baseline correction methods.
The proposed algorithm was successfully applied to experimental Raman spectral
data, and the results indicate that the baseline of Raman spectra can be
automatically subtracted.
