Face recognition using robust linear regression classification based on PCA and IGG weight function

Home > Archive>Volume 44, Issue 21, 2021 >152-157

Face recognition using robust linear regression classification based on PCA and IGG weight function
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                        Lv KaiyunLv Kaiyun
1. Faculty of Geomatics, East China University of Technology, Nanchang, 330013, China 2 Key Laboratory of Mine Environmental Monitoring and Improving around Poyang Lake, Ministry of Natural Resources, Nanchang, 330013, China
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Ju XiayiJu Xiayi
1. Faculty of Geomatics, East China University of Technology, Nanchang, 330013, China 2 Key Laboratory of Mine Environmental Monitoring and Improving around Poyang Lake, Ministry of Natural Resources, Nanchang, 330013, China
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Gong XunqiangGong Xunqiang
1. Faculty of Geomatics, East China University of Technology, Nanchang, 330013, China 2 Key Laboratory of Mine Environmental Monitoring and Improving around Poyang Lake, Ministry of Natural Resources, Nanchang, 330013, China
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Lu TiedingLu Tieding
1. Faculty of Geomatics, East China University of Technology, Nanchang, 330013, China 2 Key Laboratory of Mine Environmental Monitoring and Improving around Poyang Lake, Ministry of Natural Resources, Nanchang, 330013, China
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Affiliation:1. Faculty of Geomatics, East China University of Technology, Nanchang, 330013, China 2 Key Laboratory of Mine Environmental Monitoring and Improving around Poyang Lake, Ministry of Natural Resources, Nanchang, 330013, China
Clc Number:TP319.4
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Abstract:

Linear regression classification is a fast and effective method in face recognition. However, linear regression classification is based on image vector recognition, which leads to the fact that the original matrix image is often high-dimensional data, and the face image is often contaminated. In order to solve this problem, a robust linear regression classification algorithm based on PCA and IGG weight function is proposed in this paper. Firstly, PCA is used to reduce the dimensionality of the face image, then the IGG weight function is adopted to classify the contaminated face image. Linear regression classification, robust linear regression classification based on IGG weight function and robust linear regression classification based on PCA and IGG weight function methods are compared with the public ORL and Yale databases. The experimental results show that the average recognition rate of the proposed method is above 92.07% without noise and with salt and pepper noise and speckle noise, which are higher than the other two methods in the ORL and Yale databases.

Key words:face recognition; principal component analysis (PCA); IGG weight function; linear regression classification (LRC)

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Online: July 08,2024
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