# Characterization and Separation of Traditional and Bio-Plastics by Hyperspectral Devices
## 2 Materials and Methods
### Procedure for the Analysis of Spectrometer Data  
For the spectral characterization of plastic samples in the NIR region and extraction of the spectral signatures characterizing each material, a processing procedure is set up for the Specim Imspector spectrometer imagery.  
Hyperspectral cube creation. The combination of the images of the scene at the different wavelengths represents the hyperspectral cube, i.e., a three-dimensional array containing spatial information on the x and y axes and spectral information on the z axis.  
Radiometric calibration. This step eliminates the dependence of the measuring instruments (quantum efficiency of the sensor, filter transmission) on the spectra acquired. In fact, the spectral device does not record the reflectance of the material under investigation but rather the radiance, i.e., the amount of reflected radiation that reaches the camera sensor with energy content sufficient to be recorded. The reflectance value can be calculated only if the incident radiation on the target is known or if a suitable reference spectrum is available. In our investigation, since the incident radiation is unknown, the reflectance was calculated as the ratio of the radiance measured by the instrument and the spectrum of a Spectralon panel measured under the same lighting conditions.  
Clustering and extraction of spectral signatures. This step, performed on the radiometrically calibrated hyperspectral cube, prescribes the extraction of the spectral signature of each pixel of the cube belonging to the object under investigation. For the characterization of the materials analyzed in this work, in addition to using the curves of each individual pixel belonging to the sample, the average spectral signature of all samples is computed. The sample average spectral signature was obtained by averaging the signatures of all pixels included in a properly selected area of the sample, which is defined as Region of Interest (ROI). To emphasize the absorption peaks of the spectral signatures [12], the method of normalization of the curves defined as Continuum Removal (CR) is applied. The CR is developed for the processing of aerial and satellite images, and it has been successfully applied to the identification of the geological composition of the materials [13] and to analyze vegetation [14]. This method involves the construction of a curve that joins the maxima of the original spectral curves (hereinafter maxima curve), and the computation of the curve given by the ratio between the original and maxima curves. The reflectance peak points are then standardized to the value of 1; the reflectance value decreases toward zero as the distance between the original spectrum and the continuum line increases.  
Statistical analysis. Due to the high spectral resolution of the hyperspectral device associated with the large amount of information, spectral signatures are employed to compute the correlation matrix and thus reduce data dimensionality, highlighting the wavelengths which best differentiate the materials investigated. The correlation matrix is used by different authors for defect detection on apples [15], for feature extraction from hyperspectral data [16], for inland water quality mapping [17] and for geological unmixing classification [18].