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高光谱成像技术在烟叶杂质分类中的应用
食品检测
2026/09/21
摘要：本文提出了一种基于高光谱成像技术的烟叶杂质分类方法，通过结合savitzky-golay平滑滤波、乘性散射校正和随 机森林分类器，解决了烟叶杂质的分类问题。样本的分类精度用总体分类精度（（OA）和Kappa系数来表征，OA为99%， Kappa系数为0.987。实验结果表明，随机森林是一种优秀的高光谱数据分类器，基于高光谱成像技术的烟叶杂质分类方 法可以准确区分烟叶和烟叶中的杂质。
关键词：高光谱成像、烟草、随机森林、分类
期刊：IEEE Xplore
DOI：10.1109/IICSPI48186.2019.9095975
设备：GaiaSorter
Application of Hyperspectral Imaging Technology in Classification of Tobacco Leaves and Impurities
Abstract：In this paper, a classification method of tobacco leaves and impurities is presented, which is based on hyperspectral imaging technology. By combining savitzky-golay smoothing filter, multiplicative scatter correction and random forest classifier, the problem of the classification of tobacco leaves and impurities is overcome. The classification accuracy of the sample was characterized by the overall classification accuracy (OA) and Kappa coefficient, and the OA is 99% and the Kappa coefficient is equal to 0.987. The experimental results indicate that the random forest is an excellent hyperspectral data classifier, and the classification method of tobacco leaves and impurities based on hyperspectral imaging technology can accurately distinguish tobacco leaves and impurities which are in tobacco leaves.
Keywords：hyperspectral imaging, tobacco, random forest, Classification
