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Dorsal Hand Vein Recognition Based on Improved Bag of Visual Words Model

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Biometric Recognition (CCBR 2017)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 10568))

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Abstract

At present, the Bag of Visual Words (BoVW) model has been successfully applied to Image Retrieval and Object Recognition. However, how to build a visual dictionary with high efficiency and low redundancy is still a key issue. Therefore, in this paper, we proposed an improved BoVW model to study the dorsal hand vein recognition problem. Specifically, when constructing a visual dictionary, we first use K-means++ to obtain some clustering center points for each image category, and each center point represents a visual word. Secondly, we combine all the categories of words into a visual dictionary. Finally, we use the mutual information method to eliminate redundancy between words to optimize the visual dictionary. The proposed method was tested on image databases collected under weak constraints, and the results show that the improved model has good robustness, low computational complexity, and the expression of each image category is more prominent, so it can get better performance.

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Acknowledgment

This work was supported by the National Natural Science Fund Committee of China (NSFC no. 61673021).

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Authors and Affiliations

  1. North China University of Technology, Beijing, China

    Yiding Wang & Shan Dong

Authors
  1. Yiding Wang
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  2. Shan Dong
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Corresponding author

Correspondence to Shan Dong .

Editor information

Editors and Affiliations

  1. Tsinghua University, Beijing, China

    Jie Zhou

  2. Beihang University, Beijing, China

    Yunhong Wang

  3. Institute of Automation, Chinese Academy of Sciences, Beijing, China

    Zhenan Sun

  4. Computing and Technology, Chinese Academy of Sciences, Beijing, China

    Yong Xu

  5. Shenzhen University, Shenzhen, China

    Linlin Shen

  6. Tsinghua University, Beijing, China

    Jianjiang Feng

  7. Chinese Academy of Sciences, Beijing, China

    Shiguang Shan

  8. Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China

    Yu Qiao

  9. Graduate School at Shenzhen, Tsinghua University, Shenzhen, China

    Zhenhua Guo

  10. Shenzhen University, Shenzhen, China

    Shiqi Yu

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Wang, Y., Dong, S. (2017). Dorsal Hand Vein Recognition Based on Improved Bag of Visual Words Model. In: Zhou, J., et al. Biometric Recognition. CCBR 2017. Lecture Notes in Computer Science(), vol 10568. Springer, Cham. https://doi.org/10.1007/978-3-319-69923-3_22

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  • DOI: https://doi.org/10.1007/978-3-319-69923-3_22

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-69922-6

  • Online ISBN: 978-3-319-69923-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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