Non-negative locality-constrained vocabulary tree for finger vein image retrieval

  • Kun Su
  • Gongping Yang
  • Lu Yang
  • Peng Su
  • Yilong Yin
Research Article
  • 3 Downloads

Abstract

Finger vein image retrieval is a biometric identification technology that has recently attracted a lot of attention. It has the potential to reduce the search space and has attracted a considerable amount of research effort recently. It is a challenging problem owing to the large number of images in biometric databases and the lack of efficient retrieval schemes. We apply a hierarchical vocabulary tree model-based image retrieval approach because of its good scalability and high efficiency.However, there is a large accumulative quantization error in the vocabulary tree (VT)model thatmay degrade the retrieval precision. To solve this problem, we improve the vector quantization coding in the VT model by introducing a non-negative locality-constrained constraint: the non-negative locality-constrained vocabulary tree-based image retrieval model. The proposed method can effectively improve coding performance and the discriminative power of local features. Extensive experiments on a large fused finger vein database demonstrate the superiority of our encoding method. Experimental results also show that our retrieval strategy achieves better performance than other state-of-the-art methods, while maintaining low time complexity.

Keywords

non-negative locality-constrained vocabulary tree finger vein image retrieval large scale inverted indexing 

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Notes

Acknowledgements

This work was supported in part by the National Natural Science Foundation of China (Grant Nos. 61472226, 61573219 and 61703235), and in part by NSFC Joint Fund with Guangdong under Key Project (U1201258).

Supplementary material

11704_2017_6583_MOESM1_ESM.ppt (753 kb)
Non-negative locality-constrained vocabulary tree for finger vein image retrieval

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Copyright information

© Higher Education Press and Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  • Kun Su
    • 1
    • 2
  • Gongping Yang
    • 1
  • Lu Yang
    • 3
  • Peng Su
    • 4
  • Yilong Yin
    • 1
    • 3
  1. 1.School of Computer Science and TechnologyShandong UniversityJinanChina
  2. 2.School of Mechanical, Electrical and Information EngineeringShandong University (Weihai)WeihaiChina
  3. 3.School of Computer Science and TechnologyShandong University of Finance and EconomicsJinanChina
  4. 4.School of MathematicsDali UniversityDaliChina

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