Computer Science ›› 2019, Vol. 46 ›› Issue (6A): 274-278.

• Pattern Recognition & Image Processing • Previous Articles     Next Articles

Face Recognition Using SPCA and HOG with Single Training Image Per Person

HAN Xu1, CHEN Hai-yun1, WANG Yi2, XU Jin1   

  1. School of Electrical Engineering and Information,Southwest Petroleum University,Nanchong,Sichuan 637001,China1;
    School of Electronic and Information Engineering,Liaoning University of Engineering and Technology,Huludao,Liaoning 125105,China2
  • Online:2019-06-14 Published:2019-07-02

Abstract: Face recognition based on single sample is a challenging task.This paper combined the Similar Principal Component Analysis (SPCA) algorithm and Histograms of Oriented Gradients (HOG) algorithm,and used SPCA to screen out the similar information of the image class,and quantified the similar information blocks with HOG algorithm to make the two advantages complementary.Finally,we used Pearson correlation (PC) to identify similarity and conduct experiments on the Extended Yale B database.Experimental results show that the proposed algorithm has better recognition performance than traditional algorithm when the illumination of the face image changes.

Key words: Face recognition, Similar principal component analysis (SPCA), Histograms of oriented gradients(HOG), Pearson correlation (PC)

CLC Number: 

  • TP391
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