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Publications (2)0 Total impact

  • Lian-Wei Zhao · Si-Wei Luo · Ya-Ping Huang ·
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    ABSTRACT: This paper presents results on appearance-based three-dimensional object recognition (3DOR) accomplished by utilizing a neural network architecture developed based on Kernel Principal Component Analysis (KPCA). The basic idea of KPCA is first map the input space into a feature space via nonlinear mapping and then compute the principal component in the feature space. In this paper, we are utilizing the KPCA technique to enhance the object recognition. Through adopting a polynomial kernel, the principal component can be computed in the space spanned by high-order correlations of input pixels. The imitate results confirmed the effectiveness of the proposed method.
    Wavelet Analysis and Its Applications, and Active Media Technology - The International Computer Congress 2004; 05/2004
  • Ya-Ping Huang · Si-Wei Luo · En-Yi Chen ·
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    ABSTRACT: Iris recognition, a relatively new biometric technology, has great advantages, such as variability, stability and security, and is most promising for high security environments. A new iris recognition algorithm is proposed in this paper, which adopts Independent Component Analysis (ICA) to extract iris texture feature and a competitive learning mechanism to recognize iris patterns. Experimental results show that the algorithm is efficient and adaptive to the environment, e.g. it works well even for blurred iris images, variable illumination, and interference of eyelids and eyelashes.
    Machine Learning and Cybernetics, 2002. Proceedings. 2002 International Conference on; 02/2002