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A novel face recognition method with feature combination

  • Computer & Information Science
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Abstract

A novel combined personalized feature framework is proposed for face recognition (FR). In the framework, the proposed linear discriminant analysis (LDA) makes use of the null space of the within-class scatter matrix effectively, and Global feature vectors (PCA-transformed) and local feature vectors (Gabor wavelet-transformed) are integrated by complex vectors as input feature of improved LDA. The proposed method is compared to other commonly used FR methods on two face databases (ORL and UMIST). Results demonstrated that the performance of the proposed method is superior to that of traditional FR approaches

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Authors and Affiliations

  1. School of Computer Science and Technology, Zhejiang University, 310027, Hangzhou, China

    Li Wen-shu

  2. College of Information and Electronics, Zhejiang Sci-Tech University, 310018, Hangzhou, China

    Li Wen-shu

  3. Department of Artificial Intelligence, Xiamen University, 361005, Xiamen, China

    Zhou Chang-le

  4. Shanghai University of Traditional Chinese Medicine, 200032, Shanghai, China

    Xu Jia-tuo

Authors
  1. Li Wen-shu
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  2. Zhou Chang-le
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  3. Xu Jia-tuo
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Additional information

Project (No. 60275023) supported by the National Natural Science Foundation of China.

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Wen-shu, L., Chang-le, Z. & Jia-tuo, X. A novel face recognition method with feature combination. J. Zheijang Univ.-Sci. A 6, 454–459 (2005). https://doi.org/10.1631/jzus.2005.A0454

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  • DOI: https://doi.org/10.1631/jzus.2005.A0454

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