Novel Matrix Based Feature Extraction Method for Face Recognition Using Gaborface Features

  • Qi Zhu
  • Yong Xu
  • Yuwu Lu
  • Jiajun Wen
  • Zizhu Fan
  • Zhengming Li
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 238)


This study proposes a framework to integrate the Gaborface features and the matrix based feature extraction method for face recognition. In this framework, we first select a subset of Gaborfaces to construct the optimal ensemble Gaborface. Then, a two-phase matrix based feature extraction method, i.e.: two-dimensional linear discriminant analysis (2DLDA) plus multi-subspaces principle component analysis (MSPCA), is developed to directly and effectively extract features from the optimal ensemble Gaborface matrixes. Experiment results on ORL and AR face datasets demonstrate the effectiveness of our method.


face recognition Gaborface Gabor filter optimization matrix based feature extraction 


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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Qi Zhu
    • 1
    • 2
  • Yong Xu
    • 1
  • Yuwu Lu
    • 1
    • 2
  • Jiajun Wen
    • 1
    • 2
  • Zizhu Fan
    • 3
  • Zhengming Li
    • 4
  1. 1.Key Laboratory of Network Oriented Intelligent ComputationShenzhenChina
  2. 2.Harbin Institute of TechnologyShenzhen Graduate SchoolShenzhenChina
  3. 3.School of Basic ScienceEast China Jiaotong UniversityNanchangChina
  4. 4.Guangdong Industrial Training CenterGuangdong Polytechnic Normal UniversityGuangzhouChina

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