关键词: 近红外光谱, 主成分分析, Fisher判别分析, 非相关判别转换, 特征提取

Abstract: NIR spectroscopy analysis method is applied to classify different kinds of apple samples. A new method of apple NIR spectra qualitative analysis based on uncorrelated discriminant transformation is presented. Three methods of feature extraction such as principal component analysis, Fisher discriminant analysis and uncorrelated discriminant transformation are used to extract feature from apple NIR spectra. By using K-nearest neighbour（KNN） three classification models are constructed for the classification recognition of apples. The models are verified by using the leave-one-out cross-validation. The results show that Uncorrelated Discriminant Transformation（UDT） model, comparing with Principal Component Analysis（PCA） model and Fisher Discriminant Analysis（FDA） model, has higher accuracy recognition rate.

Key words: Near Infrared（NIR） spectroscopy, principal component analysis, Fisher discriminant analysis, uncorrelated discriminant transformation, feature extraction