Combining surface‐enhanced Raman spectroscopy and mid‐infrared spectroscopy in a data fusion model to forensic differentiate the electrostatic copying paper

Abstract

The aim of this paper was to explore the non‐destructive application of fusion spectra model for characterization and differentiation of electrostatic copying papers that could be favourable to give forensic aid in legal cases. Two hundred fifty electrostatic copy paper samples were collected from various markets. All samples were subjected to surface‐enhanced Raman spectroscopy (SERS) analysis from 3500 to 400 cm−1 Raman shift range and attenuated total reflection‐Fourier transform infrared spectrum (ATR‐FTIR) analysis from 4000 to 400 cm−1 wavenumber range, respectively. The spectral data refracted the constituents present in the electrostatic copy papers were cellulose, inorganic filler calcium carbonate and barium sulfate. Fisher discriminant analysis (FDA), multi‐class support vector machine (MSVM) and decision tree (DT) algorithms were used to build the model. The precision rate, recall rate, F‐score and total accuracy were considered as indicators to evaluate the model's performance. The results showed that fusion models were superior to single model. The feature layer fusion model based on MSVM algorithm gave a differentiating power of 100% by grouping all the sample groups. This study demonstrated that spectral fusion model is a feasible and reliable approach for fast and non‐destructive differentiation of electrostatic copying papers. It has great potential in real application scenarios.