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Appearance-based bidirectional representation for palmprint recognition

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An Erratum to this article was published on 09 November 2015

Abstract

The palmprint recognition methods can be categorized as the feature-based methods and the appearance-based methods. The conventional appearance-based representation methods merely express the test sample as a weighting sum of training samples and exploit the deviation between the test sample and the weighting sum of the training samples from each class for classification. In this paper we exploited an appearance-based palmprint recognition method called bidirectional representation method based pattern classification (BRBPC) on palmprint recognition. The BRBPC algorithm not only used the training samples to express the test sample, but also take into account the expression of the test sample to the training sample. Experiments on PolyU multi-spectral palmprint database and 2D and 3D palmprint database show that the proposed method outperforms the conventional appearance-based palmprint recognition methods.

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Authors and Affiliations

  1. Bio-Computing Research Center, Harbin Institute of Technology Shenzhen Graduate School, Shenzhen, China

    Jinrong Cui & Jiajun Wen

  2. Key Laboratory of Network Oriented Intelligent Computation, Shenzhen, China

    Jinrong Cui & Jiajun Wen

  3. School of Basic Science, East China Jiaotong University, Nanchang, China

    Zizhu Fan

Authors
  1. Jinrong Cui
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  2. Jiajun Wen
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  3. Zizhu Fan
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Correspondence to Jinrong Cui.

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Cui, J., Wen, J. & Fan, Z. Appearance-based bidirectional representation for palmprint recognition. Multimed Tools Appl 74, 10989–11001 (2015). https://doi.org/10.1007/s11042-014-1887-4

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  • DOI: https://doi.org/10.1007/s11042-014-1887-4

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