Open Access
Issue
MATEC Web Conf.
Volume 128, 2017
2017 International Conference on Electronic Information Technology and Computer Engineering (EITCE 2017)
Article Number 04015
Number of page(s) 5
Section Computer Programming
DOI https://doi.org/10.1051/matecconf/201712804015
Published online 25 October 2017
  1. Vacca J.R. Biometric Technologies and Verification Systems[M]. Butterworth-Heinemann, 2007. [Google Scholar]
  2. Kulkarni S, Raut D R. Finger Vein Recognition[J]. IOSR Journal of Electrical and Electronics Engineering (IOSR-JEEE), 2014: 32–36. [Google Scholar]
  3. Bichler O. CONVOLUTIONAL NEURAL NETWORK:, WO/2016/030230[P]. 2016. [Google Scholar]
  4. Yang J, Li X. Efficient Finger Vein Localization and RecognitionfC]// International Conference on Pattern Recognition. IEEE, 2010:1148–1151. [Google Scholar]
  5. Guan F, Wang K, Yang Q. A study of two direction weighted (2D)2LDA for finger vein recognition[C]// International Congress on Image and Signal Processing. IEEE, 2011: 860–864. [Google Scholar]
  6. Yang W, Rao Q, Liao Q. Personal Identification for Single Sample Using Finger Vein Location and Direction Coding[C]// International Conference on Hand-Based Biometrics. IEEE, 2011:1–6. [Google Scholar]
  7. Gupta P, Gupta P. An accurate finger vein based verification system[J]. Digital Signal Processing, 2015, 38:43–52. [CrossRef] [EDP Sciences] [Google Scholar]
  8. Wu J D, Liu C T. Finger-vein pattern identification using principal component analysis and the neural network technique[J]. Expert Systems with Applications, 2011, 38(5):5423–5427. [CrossRef] [Google Scholar]
  9. Wang K Q, Khisa A S, Wu X.Q, et al. Finger vein recognition using LBP variance with global matching[C]// International Conference on Wavelet Analysis and Pattern Recognition. IEEE, 2012:196–201. [Google Scholar]
  10. Hubel D H, Weisel T N. Wiesel, T.N.: Receptive fields, binocular interaction and functional architecture in cat’s visual cortex. J. Physiol. (London) 160, 106–154[J]. 1962, 160. [CrossRef] [PubMed] [Google Scholar]
  11. Breu H, Gil J, Kirkpatrick D, et al. Linear time Euclidean distance transform algorithms[J]. IEEE Transactions on Pattern Analysis & Machine Intelligence, 2002, 17(5):529–533. [CrossRef] [Google Scholar]
  12. Yuan Z W, Zhang J. Feature extraction and image retrieval based on AlexNet[C]// Eighth International Conference on Digital Image Processing. 2016:100330E. [Google Scholar]
  13. Liu W, Wen Y, Yu Z, et al. Large-Margin Softmax Loss for Convolutional Neural Networks[J]. 2016. [Google Scholar]
  14. http://www.datatang.com [Google Scholar]
  15. Jia, Yangqing, Shelhamer, et al. Caffe: Convolutional Architecture for Fast Feature Embedding[J]. 2014:675–678. [EDP Sciences] [Google Scholar]
  16. Neyshabur B, Salakhutdinov R, Srebro N. Path-SGD: Path-Normalized Optimization in Deep Neural Networks[J]. Computer Science, 2015. [Google Scholar]
  17. Liu Z et al. Finger vein recognition with manifold learning. Journal of Network and Computer Applications. 2010; 33(3):275–82. [CrossRef] [Google Scholar]
  18. Perez Vega A, Travieso CM, Alonso JB. Biometric personal identi cation system based on patterns created by nger veins. 2014 International Work Conference on Bio-inspired Intelligence (IWOBI), IEEE. 2014. [Google Scholar]
  19. Dong S, Yang J, Chen Y, et al. Finger Vein Recognition Based on Multi-Orientation Weighted Symmetric Local Graph Structure[J]. Ksii Transactions on Internet & Information Systems, 2015, 9(10):4126–4142. [Google Scholar]
  20. Xie S J, Lu Y, Yoon S, et al. Intensity Variation Normalization for Finger Vein Recognition Using Guided Filter Based Singe Scale Retinex.[J]. Sensors, 2015, 15(7):17089–17105. [CrossRef] [Google Scholar]

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