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发表时间：2008-01-01

发表刊物：模式识别与人工智能

所属单位：机械工程学院

期号：2

页面范围：160-164

ISSN号：1003-6059

摘要：A method for infrared face recognition is proposed based on principal component analysis (PCA) and linear discriminant analysis (LDA). According to the characteristics of infrared face images, a set of normalized infrared face images is gotten by preprocessing. The dimensionality of the image vector is reduced and the global features are extracted. The global features are used to generate a classifier which can minimize the within-class scatter and maximize the between-class scatter. Finally, an infrared face recognition experiment based on the combination of PCA and LDA is performed and the results show the high performance of the proposed method.

备注：新增回溯数据