Electronic Science and Technology ›› 2019, Vol. 32 ›› Issue (7): 43-48.doi: 10.16180/j.cnki.issn1007-7820.2019.07.009

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Face Recognition Algorithm Based on Multiple Feature Fusion

SU Rao,LI Feifei,CHEN Qiu   

  1. School of Optical Electrical and Computer Engineering,University of Shanghai for Science and Technology,Shanghai 200093,China
  • Received:2018-07-16 Online:2019-07-15 Published:2019-08-14
  • Supported by:
    The Program for Professor of Special Appointment (Eastern Scholar) at Shanghai Institutions of Higher Learning(ES2015XX)


The texture information extracted by the LBP descriptor and the edge feature extracted by the GMQ operator cannot effectively and comprehensively describe the facial feature. To solve the problems, a novel multiple feature fusion algorithm based on Markov Stationary Features model was proposed. Firstly, the edge features obtained by GMQ operator as well as the texture features by LBP descriptor were fused with the MSF model respectively. Then the two MSF-based features were fused by linear weighting. Finally, experiments on the ORL dataset showed that the proposed algorithm could achieve an accuracy of 95.83%. Compared with a single feature extraction algorithm and a common face recognition algorithm, the effectiveness of the proposed method was proved.

Key words: face recognition, local binary pattern, gradient magnitude quantization, markov stationary features, linear weighting fusion, ORL database

CLC Number: 

  • TP391.41