• DocumentCode
    2650714
  • Title

    Research of face image recognition based on probabilistic neural networks

  • Author

    Ni Qiakai ; Guo Chao ; Yang Jing

  • Author_Institution
    Coll. of Inf. Eng., Taiyuan Univ. of Technol., Taiyuan, China
  • fYear
    2012
  • fDate
    23-25 May 2012
  • Firstpage
    3885
  • Lastpage
    3888
  • Abstract
    This paper introduces the principle of probabilistic neural networks (PNN) algorithm and its application in face image recognition. After wavelet decomposition and discrete cosine transform, the image features of face image are extracted. Then the features are sent respectively into BP neural networks, LVQ neural networks and PNN neural networks for image recognition. ORL face image database is used in simulation experiments. Through analyzing and comparing the simulation results and recognition accuracy, conclusions are obtained of the advantage and characteristic of each neural networks. PNN neural networks show the highest recognition accuracy, thus it can be the optimal choice for image recognition.
  • Keywords
    discrete wavelet transforms; face recognition; feature extraction; radial basis function networks; BP neural networks; LVQ neural networks; ORL face image database; PNN neural networks; discrete cosine transform; face image recognition; feature extraction; probabilistic neural networks; recognition accuracy; simulation experiments; wavelet decomposition; Biological neural networks; Face; Face recognition; Image recognition; Training; Discrete Cosine Transform; Face Image Recognition; Probabilistic Neural Networks; Wavelet Decomposition;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Control and Decision Conference (CCDC), 2012 24th Chinese
  • Conference_Location
    Taiyuan
  • Print_ISBN
    978-1-4577-2073-4
  • Type

    conf

  • DOI
    10.1109/CCDC.2012.6243102
  • Filename
    6243102