A Method of Distinguishing Tea varieties Based on Hyperspectral Imaging. (August 2020)

• Record Type: Journal Article
• Authors: Yanqi, Zhong; Zhiliang, Kang; Peng, Wang; Xiong, Luo
• Is Part Of: Journal of physics. Volume 1617(2020)
• Publication Date: 2020-08
• Subjects: Physics -- Congresses; 530.5
• DOI: 10.1088/1742-6596/1617/1/012061
• Languages: English
• ISSNs: 1742-6588

Abstract

Abstract: In order to realize the rapid and non-destructive identification of tea varieties, this paper based on hyperspectral imaging technology to find the optimal discrimination model of tea varieties. This article is mainly divided into three aspects: the discriminant model of tea varieties based on spectral characteristics, the discriminant model of tea varieties based on image features, and the discriminant model of tea varieties based on spectral-image fusion features. The experimental results show that Model 1 uses the full-spectrum feature combined with support vector machine (SVM) model, which can distinguish the accuracy of different tea varieties up to 100%. Model 2 is based on the GLCM texture feature based on the characteristic gray image combined with the SVM model, and the discrimination accuracy of different tea varieties reaches 100%. Model 3 discusses the impact of different preprocessing methods on the accuracy of classification under the fusion of two information features, determines Minmax as the best preprocessing method, and obtains 100% classification accuracy in the test set.