Application of hyperspectral imaging technology to tobacco leaf and foreign matter sorting

In order to improve the quality of cigarettes and to reject foreign matters from tobacco leaves during cigarette manufacturing, a tobacco leaf and foreign matter sorting method was established on the basis of hyperspectral imaging technology combined with Savitzky-Golay (SG) smoothing filter, multiple scattering correction (MSC) and support vector machine (SVM). The sorting accuracy was characterized by the overall sorting accuracy (OA) and Kappa coefficient. The experimental results showed that the sorting effect was the best when radial basis function was adopted. The overall tobacco and foreign matter sorting accuracy reached 99.92% with the Kappa coefficient of 0.998. The sorting method based on hyperspectral imaging technology can accurately distinguish plastic, rubber or metal products from tobacco leaves.