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Indexed by:期刊论文

Date of Publication:2022-06-29

Journal:大连理工大学学报

Affiliation of Author(s):机械工程学院

Issue:1

Page Number:62-66

ISSN No.:1000-8608

Abstract:Thermal infrared face image recognition is studied by combining linear dimensionality reduction technology and BP neural network. First, the methods of principal component analysis and linear discriminant analysis are adopted to reduce the dimensionality of thermal infrared face images and extract feature vectors from thermal infrared face images. Then, the feature vectors are used for BP neural network training, and a classifier with strong robust and fault tolerance can be generated for thermal infrared face image recognition. Experimental results show that the method can get a high recognition rate for thermal infrared face image because BP neural network is used as a classifier instead of the Euclidian distance metric for discrimination between feature vectors.

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