吉林大学学报(工学版) ›› 2013, Vol. 43 ›› Issue (04): 1121-1126.doi: 10.7964/jdxbgxb201304044

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Noisy face images recognition based on relevance vector machine

LIU Chang-yuan1,2, BI Xiao-jun1, Wei Qi2   

  1. 1. College of Information and Communication Engineering, Harbin Engineering University, Harbin 150001, China;
    2. College of Electrical and Electronic Engineering, Harbin University of Science and Technology, Harbin 150080, China
  • Received:2012-07-22 Online:2013-07-01 Published:2013-07-01

Abstract:

A new method of face recognition based on relevance vector machine was developed. After the wavelet decomposition and Principal Component Analysis (PCA) transformation, the relevance vectors from sample training constitute a "hyperplane" as the differences in the classification of the samples by machine learning algorithm. The "one against one" method is used to achieve multi-class pattern recognition. Compared with former methods, a large number of simulation results of recognition of noisy objects show that the new method is not sensitive to image noise, with high recognition accuracy and strong robustness.

Key words: information processing, face recognition, relevance vector machine, image noise

CLC Number: 

  • TN911

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