Identification of Hazardous Substances in Mail by Terahertz Radiation Based on Voigt and AsLS Fitting Spectral Reconstruction - Tao Li; Yungao Gu; Chao Wang; Yiyang Yao; Ying Zhang; Yajie Guo; Dayong Gu (International Journal of Optics)
With the development of e-commerce, noninvasive mail inspection is becoming particularly prominent. Terahertz waves have fingerprint spectrum characteristics and can penetrate nonpolar materials. Terahertz waves are ideal for the nondestructive identification of harmful substances hidden in the mail. However, the gaps between mail packages and samples affect the accuracy of the inspection. In this study, the influence of irregular gaps was analyzed using a model sample under envelope occlusion. A spectral reconstruction method based on Voigt and asymmetric least squares (AsLS) fitting is proposed. Principal component analysis (PCA) results showed that the reconstructed spectral data were easier to identify and the root mean square error (RMSE) of quantitative analysis was the smallest. PCA–support vector machine (SVM) and convolutional neural network (CNN) classification models were used to verify the effectiveness of this method.