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Palmprint Recognition Using Discriminant Local Line Directional Representation

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Advanced Computational Methods for Knowledge Engineering (ICCSAMA 2019)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1121))

Abstract

Palmprint is a new biometric feature for personal identification with a high degree of privacy and security. In this paper, we propose the palmprint feature extraction method which combines the direction-based method (Local line direction pattern) and learning-based method (two-directional two-dimensional linear discriminant analysis ((2D)2LDA)) to get the high discriminant direction based features, so-called Discriminant local line Directional Representation (DLLDR). First, the algorithm computes the LLDP features with two strategies of encoding multi-directions. Then, (2D)2LDA is applied to extract DLLDR features with higher discriminant and lower-dimensional from the LLDP matrix. The experimental results on the public databases of Hong Kong Polytechnic University demonstrate that our method is effective for palmprint recognition.

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Acknowledgments

The authors would like to thank the Saigon International University (SIU) for funding this project.

Author information

Authors and Affiliations

  1. The Saigon International University (SIU), Ho Chi Minh City, Vietnam

    Hoang Thien Van & Quynh Pham Thi

  2. University of Information Technology (UIT), Vietnam National University, Ho Chi Minh City, Vietnam

    Kiet Dang Hung

  3. University of People’s Security, Ho Chi Minh City, Vietnam

    Giang Vu Van

  4. University of Sciences, Vietnam National University, Ho Chi Minh City, Vietnam

    Thai Hoang Le

Authors
  1. Hoang Thien Van
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  2. Kiet Dang Hung
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  3. Giang Vu Van
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  4. Quynh Pham Thi
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  5. Thai Hoang Le
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Corresponding author

Correspondence to Hoang Thien Van .

Editor information

Editors and Affiliations

  1. Computer Science and Applications Department LGIPM, University of Lorraine, Metz Cedex 03, France

    Hoai An Le Thi

  2. Computer Science and Applications Department LGIPM, University of Lorraine, Metz Cedex 03, France

    Hoai Minh Le

  3. Laboratory of Mathematics, National Institute for Applied Sciences, Saint-Étienne-du-Rouvray Cedex, France

    Tao Pham Dinh

  4. Department of Information Systems, Wroclaw University of Science and Technology, Wrocław, Poland

    Ngoc Thanh Nguyen

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Van, H.T., Hung, K.D., Van, G.V., Thi, Q.P., Le, T.H. (2020). Palmprint Recognition Using Discriminant Local Line Directional Representation. In: Le Thi, H., Le, H., Pham Dinh, T., Nguyen, N. (eds) Advanced Computational Methods for Knowledge Engineering. ICCSAMA 2019. Advances in Intelligent Systems and Computing, vol 1121. Springer, Cham. https://doi.org/10.1007/978-3-030-38364-0_19

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